Papers of BI

• Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning, I. Hwang, Y. Kwak, S. Choi, B.-T. Zhang, S. Lee, The 41th International Conference on Machine Learning (ICML 2024), July 2024.
• On Positivity Condition for Causal Inference, I. Hwang*, Y. Choe*, Y. Kwon, S. Lee, The 41th International Conference on Machine Learning (ICML 2024), July 2024. (* equal contribution)
• Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction, Y. Kwak*, I. Hwang*, D. Kim, S. Lee, B.-T. Zhang, The 40th Conference on Uncertainty in Artificial Intelligence (UAI 2024), July 2024. (* equal contribution) (oral presentation, acceptance ratio=3.8%)
• Multi-Object RANSAC: Efficient Plane Clustering Method in a Clutter, S. Lim, Y. Yoo, J.-K. Lee B.-T. Zhang, In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2024), May 2024. [PDF]
• HAPFI: History-Aware Planning based on Fused Information, S. Jeon, S. Shin, B.-T. Zhang, In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2024), May 2024. [PDF]
• PROGrasp: Pragmatic Human-Robot Communication for Object Grasping, G.-C. Kang, J. Kim, J. Kim, B.-T. Zhang, In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2024), May 2024. [PDF]
• Unveiling the Significance of Toddler-Inspired Reward Transition in Goal-Oriented Reinforcement Learning, J. Park, H.-B. Yoo, Y. Kim, M.-W. Lee, K. Kim, W.-S. Choi, M. Lee, B.-T. Zhang, In Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), Feb 2024. (oral presentation) [PDF]
• DUEL: Duplicate Elimination on Active Memory for Self-supervised Class-imbalanced Learning, W.-S. Choi, H. Lee, D.-S. Han, J. Park, H. Koo, B.-T. Zhang, In Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), Feb 2024. [PDF]

• Quantized Local Independence Discovery for Fine-Grained Causal Dynamics Learning in Reinforcement Learning, I. Hwang, Y. Kwak, S. Choi, B.-T. Zhang, S. Lee, NeurIPS 2023 Workshop on Generalization in Planning, Dec 2023. [PDF]
• Domain adapted broiler density map estimation using negative-patch data augmentation, T. Kim, D.-H. Lee, W.-S. Kim, B.-T. Zhang, Biosystesm Engineering, 231, 865-177, 2023. [PDF]
• Video Turing Test: A first step towards human-level AI, M. Lee, Y.-J. Heo, S. Choi, W.-S. Choi, B.-T. Zhang, AI Magazie, 44, 537-554, 2023. [PDF]
• GVCCI: Lifelong Learning of Visual Grounding for Language-Guided Robotic Manipulation, J. Kim, G.-C. Kang, J. Kim, S. Shin, B.-T. Zhang, In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023), Oct 2023. [PDF]
• EXOT: Exit-aware Object Tracker for Safe Robotic Manipulation of Moving Object, H. Kim, H.-J. Yoon, M. Kim, D.-S. Han, B.-T. Zhang, In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA 2023), May 2023. [PDF]
• Robust Map Fusion with Visual Attention Utilizing Multi-agent Rendezvous, J. Kim, D.-S. Han, B.-T. Zhang, In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA 2023), May 2023. [PDF]
• The Dialog Must Go On: Improving Visual Dialog via Generative Self-Training, G.-C. Kang, S. Kim*, J.-H. Kim*, D.-H. Kwak*, B.-T. Zhang, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), June 2023. (* equal contribution) [PDF]
• Learning Geometry-aware Representations by Sketching, H. Lee, I. Hwang, H. Go, W.-S. Choi, K. Kim, B.-T. Zhang, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), June 2023. [PDF]
• On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition, I. Hwang, Y. Kwak, Y.-J. Song, B.-T. Zhang, S. Lee, Conference on Causal Learning and Reasoning (CLeaR), April 2023. [PDF]
• Mothers' use of touch across infants' development and its implications for word learning: Evidence from Korean dyadic interactions,
  E.-S.Ko, R.Abu-Zhaya, E.-S.Kim, T.Kim, K.-W.On, H.Kim, B.-T.Zhang, A.Seidl, International Congress of Infant Studies, July 2023. [PDF]

• Team Tidyboy at the WRS 2020: a modular software framework for home service robots, T. Kang, D.-W Song, J. Yi, J.-Y. Kim, C.-Y. Lee, Y. Yoo, M. Kim, H.-J. Jo, B.-T. Zhang, J. Song, and S.-J. Yi, Team Tidyboy at the WRS 2020: a modular software framework for home service robots, Advanced Robotics, 36:17-18, 836-849, 2022. [PDF]
• PlaceNet: Neural Spatial Representation Learning with Multimodal Attention, C.-Y.Lee, Y.Yoo, B.-T.Zhang, The 31th International Joint Conference on Artificial Intelligence (IJCAI 2022), July 2022. [PDF]
• SelecMix: Debiased Learning by Contradicting-pair Sampling,
  I. Hwang, S.-J.Lee, Y.-H.Kwak, S.-J.Oh, D.Teney, J.-H.Kim, B.-T.Zhang, Advances in Neural Information Processing Systems 35 (NeurIPS 2022), November 2022. [PDF]
• Robust Imitation via Mirror Descent Inverse Reinforcement Learning, D.-S.Han, H.-S.Kim, H.-D.Lee, J.-H.Ryu, B.-T.Zhang, Advances in Neural Information Processing Systems 35 (NeurIPS 2022), November 2022. [PDF]
• Modal-specific Pseudo Query Generation for Video Corpus Moment Retrieval, M. Jung, S. Choi, J. Kim, J.-H. Kim, B.-T. Zhang, In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), December 2022. [PDF]
• From Scratch to Sketch: Deep Decoupled Hierarchical Reinforcement Learning for Robotic Sketching Agent, G.-H.Lee, M.-J.Kim, M.Lee, B.-T.Zhang, In Proceedings of the 2022 IEEE International Conference on Robotics and Automation (ICRA 2022), May 2022. [PDF]
• Hypergraph Transformer: Weakly-Supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering, Y.-J.Heo, E.-S.Kim, W.-S.Choi, B.-T.Zhang, In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), May 2022. [PDF]
• Smooth-Swap: A Simple Enhancement for Face-Swapping with Smoothness, J.-S.Kim, J.-H.Lee, B.-T.Zhang, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2022), June 2022. [PDF]
• DUEL: Adaptive Duplicate Elimination on Working Memory for Self-Supervised Learning, W.-S. Choi, D.-S. Han, H. Lee, J. Park, B.-T.Zhang, Neural Information Processing Systems Workshops, December 2022. [PDF]
• Language-agnostic Semantic Consistent Text-to-Image Generation, S.-J. Jung, W.-S. Choi, S. Choi, B.-T. Zhang, In Proceedings of the Workshop on Multilingual Multimodal Learning (ACL 2022), May 2022. [PDF]
• Scene Graph Parsing via Abstract Meaning Representation in Pre-trained Language Models, W.-S. Choi, Y.-J. Heo, D. Punitan, B.-T. Zhang, In Proceedings of the 2nd Workshop on Deep Learning on Graphs for Natural Language Processing (DLG4NLP 2022), July 2022. [PDF]
• On the Importance of Critical Period in Multi-stage Reinforcement Learning, J. Park, I. Hwang, M.-W. Lee, H. Oh, M. Lee, B.-T. Zhang, In Proceedings of the ICML Complex Feedback in Online Learning Workshop (ICML 2022), July 2022. [PDF]
• Improving Robustness to Texture Bias via Shape-focused Augmentation, S.-J.Lee, I. Hwang, G.-C.Kang, B.-T. Zhang, Computer Vision and Pattern Recognition Workshops (CVPRW), June 2022. [PDF]
• Editorial: Task planning and motion control problems of service robots in human-centered environments, H.Moon, B.-T.Zhang, C.Nam Intell. Serv. Robotics 15(4): 439-440, 2022

• C^3: Contrastive Learning for Cross-domain Correspondence in Few-shot Image Generation, H. Lee, G.-C Kang, C.-H Jeong, H. Sul, B. -T. Zhang, NeurIPS 2021 Workshop on Controllable Generative Modeling in Language and Vision (CtrlGen), 2021. [PDF]
• Partition-based Local Independence Discovery, I. Hwang, B.-T. Zhang, S. Lee, Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice (NeurIPS 2021 Workshop), December 2021.
• M2FN: Multi-step modality fusion for advertisement image assessment, K.-W. Park, J.-W. Ha, J.-H. Lee, S.-Y. Kwon, K.-M. Kim, B.-T. Zhang, Applied Soft Computing, 103, 107116, May 2021. [PDF]
• Data-driven experimental design and model development using Gaussian process with active learning, J. Chang, J.-S. Kim, B.-T. Zhang, M. A. Pitt, J. I. Myung, Cognitive Psychology, 125, 101360, 2021. [PDF]
• Leveraging node neighborhoods and egograph topology for better bot detection in social graphs, B. Bebensee, N. Nazarov, B.-T. Zhang, Social Network Analysis and Mining, 11(1), 1-14, January 2021. [PDF]
• Toward a Human-Level Video Understanding Intelligence, Y. -J. Heo, M. Lee, S. Choi, W. -S. Choi, M. Shin, M. Jung, J. -K. Ryu, B.-T.Zhang, Proceedings of the 2021 AAAI 2021 Fall Symposium (AAAI FSS 2021), 2021. [PDF]
• Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning, K.Kim, M.W.Lee, Y.Kim, J.-H.Ryu, M.Lee, B.-T.Zhang, Advances in Neural Information Processing Systems 34 (NeurIPS 2021), December 2021. [PDF]
• Toddler-Guidance Learning: Impacts of Critical Period on Multimodal AI Agents, J. -S. Park, K. -Y. Park, H. -S. Oh, G. -H. LEE, M. -S. LEE, Y. -K. Lee, B. -T. Zhang, 23rd ACM International Conference on Multimodal Interaction (ICMI2021), October 2021. (oral presentation, accept ratio= 13%) [PDF]
• Passive Versus Active: Frameworks of Active Learning for Linking Humans to Machines, J. Lim, H. Jo, B.-T. Zhang, J. Park, In Proceedings of the 43rd Annual Meeting of the Cognitive Science Society (CogSci 2021), 2021. [PDF]
• Devil’s Advocate: Novel Boosting Ensemble Method from Psychological Findings for Text Classification, H. Jo, J. Lim, B.-T. Zhang, In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), August 2021. [PDF]
• Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer, G.-C. Kang, J. Park, H. Lee, B.-T. Zhang, J.-H. Kim, In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), August 2021. [PDF]
• Attend What You Need: Motion-Appearance Synergistic Networks for Video Question Answering, A.-J. Seo, G.-C. Kang, J.-H. Park, B.-T. Zhang, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), August 2021.
• Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning, T. Kim, I. Hwang, H.-D. Lee, H. Kim, W.-S. Choi, J. Lim, B.-T. Zhang, The 38th International Conference on Machine Learning (ICML 2021), July 2021.
• Co-attentional Transformers for Story-Based Video Understanding, B. Bebensee, B.-T. Zhang, In Proceedings of the 46th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), June 2021. [PDF]
• Multimodal Anomaly Detection Based on Deep Auto-Encoder for Object Slip Perception of Mobile Manipulation Robots, Y.-J. Yoo, C.-Y. Lee, B.-T. Zhang, In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), June 2021.
• DramaQA: Character-Centered Video Story Understanding with Hierarchical QA, S.-H. Choi, K.-W. On, Y.-J Heo, A.-J. Seo, Y.-W. Jang, M.-S. Lee and B.-T. Zhang, Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021. [PDF]
• Passive Versus Active: Frameworks of Active Learning for Linking Humans to Machines, J. Lim, H. Jo, B.-T. Zhang, J. Park, Proceedings of the 43rd Annual Meeting of the Cognitive Science Society (CogSci 2021), 2021.

• Hypergraph Attention Networks for Multimodal Learning, E.-S. Kim, W.-Y. Kang, K.-W. On, Y.-J. Heo and B.-T. Zhang, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR, 2020), June 2020. [PDF]
• Label Propagation Adaptive Resonance Theory for Semi-Supervised Continuous Learning, T. Kim, I. Hwang, G.-C. Kang, W.-S. Choi, H. Kim and B.-T. Zhang, In Proceedings of the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), May 2020. [PDF]
• Cut-Based Graph Learning Networks to Discover Compositional Structure for Sequential Video Data, K.-W. On, E.-S. Kim, Y.-J Heo and B.-T. Zhang, In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), Feb 2020. (oral presentation, accept ratio=5.8%) [PDF]
• Toward General Scene Graph: Integration of Visual Semantic Knowledge with Entity Synset Alignment, W.-S. Choi, K.-W. On, Y.-J. Heo and B.-T. Zhang, ACL 2020 Workshop on Advances in Language and Vision Research, July 2020. [PDF]
• Hierarchical Color Learning in Convolutional Neural Networks, C. Hickey and B.-T. Zhang, CVPR-20 Workshop on Minds vs Machines, June 2020. [PDF]

• Bayesian evolutionary hypernetworks for interpretable learning from high-dimensional data, S.-J. Kim, J.-W. Ha, H. Kim, and B.-T. Zhang, Applied Soft Computing Journal, 81, 105477, August 1, 2019. [PDF]
• Enzymatic weight update algorithm for DNA-based molecular learning, C. Baek, S.-W. Lee, B.-J. Lee, D.-H. Kwak, and B.-T. Zhang, Molecules, 24, 1409, April 10, 2019. [PDF]
• Dual Attention Networks for Visual Reference Resolution in Visual Dialog, G.-C. Kang, J. Lim, and B.-T. Zhang, In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019), pp. 2024-2033, 2019. [PDF]
• Spatial Perception by Object-Aware Visual Scene Representation, C. Y. Lee, H. Lee, I. Hwang, and B. T. Zhang, In Proceedings of the IEEE International Conference on Computer Vision Workshop (ICCVW 2019), 2019. [PDF]
• WithDorm: Dormitory Solution forLinking Roommates, T. Kim, M. Kwak, S. H. Yang, J. Lim, and B. T. Zhang, In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2019), pp. 38:1-38:6. ACM, 2019. [PDF]
• CoDraw: Collaborative drawing as a testbed for grounded goal-driven communication, J.-H. Kim, N. Kitaev, X. Chen, M. Rohrbach, B.-T. Zhang, Y. Tian, and D. Batra, In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), pp. 6495-6513, 2019. [PDF]
• Simulating problem difficulty in arithmetic cognition through dynamic connectionist models, S. Cho, J. Lim, C. Hickey, J. A. Park, and B.-T. Zhang, In Proceedings of the 17th International Conference on Cognitive Modeling (ICCM 2019), pp. 29-34, 2019. [PDF]
• Modeling delay discounting using Gaussian process with active learning, J. Chang, J. Kim, B.-T. Zhang, M. A. Pitt, and J. I. Myung, In Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019), pp. 1479-1485, 2019. [PDF]
• Problem difficulty in arithmetic cognition: Humans and connectionist models, S. Cho, J. Lim, C. Hickey, and B.-T. Zhang, In Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019), pp. 1506-1512, 2019. [PDF]
• Compositional structure learning for sequential video data, K.-W. On, E.-S. Kim, Y.-J. Heo, and B.-T. Zhang, Learning and Reasoning with Graph-Structured Representations, ICML 2019, 2019. [PDF]
• Constructing hierarchical Q&A datasets for video story understanding, Y.-J. Heo, K.-W. On, S. Choi, J. Lim, J. Kim, J.-K. Ryu, B.-C. Bae, and B.-T. Zhang, Story-Enabled Intelligence, AAAI Spring Symposium 2019 (AAAI SSS-19), 2019. [PDF]
• Visualizing semantic structures of sequential data by learning temporal dependencies, K.-W. On, E.-S. Kim, Y.-J. Heo, and B.-T. Zhang, AAAI-19 Workshop on Network Interpretability for Deep Learning, 2019. [PDF]
• Data interpolations in deep generative models under non-simply-connected manifold topology, J. Kim, and B.-T. Zhang, AAAI-19 Workshop on Network Interpretability for Deep Learning, 2019. [PDF]

• Identifying DNA methylation modules associated with a cancer by probabilistic evolutionary learning, J.-K. Rhee, S.-J. Kim, and B.-T. Zhang, IEEE Computational Intelligence Magazine, Auguest 2018. [PDF]
• Molecular associative memory with spatial auto-logistic model for pattern recall, D. Punithan, and B.-T. Zhang, Procedia Computer Science, 123: 373–379, 2018. [PDF]
• Generative local metric learning for nearest neighbor classification, Y.-K. Noh, B.-T. Zhang, and D.-D. Lee, IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(1): 106-118, 2018. [PDF]
• Fluid dynamic models for Bhattacharyya-based discriminant analysis, Y.-K. Noh, F. C. Park, B.-T. Zhang, and D.-D. Lee, IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(1): 92-105, 2018. [PDF]
• Answerer in questioner's mind: Information theoretic approach to goal-oriented visual dialog, S.-W. Lee, Y.-J. Heo, and B.-T. Zhang, The 32nd Annual Conference on Neural Information Processing Systems (NIPS 2018), 2018. (Spotlight presentation, accept ratio = 4.07%) [PDF] [arXiv]
• Bilinear attention networks, J.-H. Kim, J. Jun, and B.-T. Zhang, The 32nd Annual Conference on Neural Information Processing Systems (NIPS 2018), 2018. (spolight) [PDF] [arXiv]
• Molecular associative memory for pattern recall with local neighborhood model, D. Punithan, and B.-T. Zhang, The 24th International Conference on DNA Computing and Molecular Programming (DNA 2018), 2018. [PDF] (to be pulished)
• Multimodal dual attention memory for video story question answering, K. Kim, S.-H. Choi, J.-H. Kim, and B.-T. Zhang, The 15th European Conference on Computer Vision (ECCV 2018), 2018. [PDF]
• Lifelong learning with the feedback-loop between emotions and actions via intrinsic reward, D. Punithan, and B.-T. Zhang, Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2018), 2018. [PDF] (to be pulished)
• Robust human following by deep Bayesian trajectory prediction for home service robots, B.-J. Lee, J. Choi, C. Baek, and B.-T. Zhang, 2018 IEEE International Conference on Robotics and Automation (ICRA 2018), 2018. [PDF]
• Temporal attention mechanism with conditional inference for large-scale multi-label video classification, E.-S. Kim, J. Kim, K.-W. On, Y.-J. Heo, S.-H. Choi, H.-D. Lee, and B.-T. Zhang, The 2nd Workshop on YouTube-8M Large-Scale Video Understanding, ECCV 2018, 2018. [PDF]
• Bilinear attention networks for VizWiz challenge, J.-H. Kim, Y. Choi, S. Hong, J. Jun, and B.-T. Zhang, VizWiz Grand Challenge: Answering Visual Questions from Blind People, ECCV 2018, 2018. [PDF]
• Contextualized bilinear attention networks, G.-C. Kang, S. Son, and B.-T. Zhang, VizWiz Grand Challenge: Answering Visual Questions from Blind People, ECCV 2018, 2018. [PDF]
• VLAS: A vision-language-action integrated system for mobile social service robot, K.-W. Park, J.-Y. Choi, B.-J. Lee, C.-Y. Lee, I. Hwang, and B.-T. Zhang, Federated AI for Robotics Workshop (FAIR) 2018, IJCAI 2018, 2018. [PDF]
• GLAC Net: GLocal attention cascading networks for multi-image cued story generation, T. Kim, M.-O. Heo, S. Son, K.-W. Park, and B.-T. Zhang, Storytelling Workshop, NAACL 2018, 2018. [PDF] [code] (1st place in Visual Storytelling Challenge 2018)
• Perception-action-learning system for mobile social-service robots using deep learning, B.-J. Lee, J. Choi, K.-W. Park, C.-Y. Lee, S. Choi, C. Han, D.-S. Han, C. Baek, P. Emaase and B.-T. Zhang, AAAI-18 Demonstrations Program, 2018. [PDF] (Best Technical Demonstration)

• In vitro molecular machine learning algorithm via symmetric internal loops of DNA, J.-H. Lee, S.H. Lee, C. Baek, H.-S. Chun, J.-H. Ryu, J.-W. Kim, R. Deaton, and B.-T. Zhang, Biosystems, 158:1-9, 2017. [PDF]
• Dual-memory neural networks for modeling cognitive activities of humans via wearable sensors, S.-W. Lee, C.-Y. Lee, D.-H. Kwak, J.-W. Ha, J. Kim, and B.-T. Zhang, Neural Networks, 92:17-28, 2017. [PDF]
• Lifelong Autonomous Learning through Intrinsic Motivation and Emergent Emotions in Embodied Agents, D. Punithan, and B.-T. Zhang, International Symposium on Perception, Action, and Cognitive Systems (PACS 2017), 2017. (poster, Best Paper Award)
• Overcoming catastrophic forgetting by incremental moment matching, S.-W. Lee, J.-H. Kim, J. Jun, J.-W. Ha, and B.-T. Zhang, Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017. (Spotlight presentation, accept ratio = 4.7%). [PDF][arXiv]
• A novel method to monitor human stress states using ultra-short-term ECG spectral feature, B. Hwang, J. W. Ryu, C. Park, and B.-T. Zhang, The 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2017), 2017. [PDF]
• Extremely sparse deep learning using inception modules with dropfilters, W.-Y. Kang, K.-W. Park, and B.-T. Zhang, The 14th IAPR International Conference on Document Analysis and Recognition (ICDAR 2017), 2017. [PDF]
• Molecular associative memory with spatial auto-logistic model for pattern recall, D. Punithan, and B.-T. Zhang, The 8th Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2017), 2017. [PDF]
• DeepStory: Video story QA by deep embedded memory networks, K.-M. Kim, M.-O. Heo, S.-H. Choi, and B.-T. Zhang, The 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), 2017. (Invited paper to UAI 2017 MLTrain’s “Neural Abstract Machines” session) [PDF]
• Answerer in questioner’s mind for goal-oriented visual dialogue, S.-W. Lee, Y. Heo, and B.-T. Zhang, NIPS 2017 Workshop on Visually-Grounded Interaction and Language (ViGIL), 2017 [PDF]
• Visual explanations from Hadamard product in multimodal deep networks, J.-H. Kim, and B.-T. Zhang, NIPS 2017 Workshop on Visually-Grounded Interaction and Language (ViGIL), 2017 [PDF]
• Into the colorful world of webtoons: Through the lens of neural networks, C. Cinarel, and B.-T. Zhang, ICDAR 2017 Workshop on coMics ANalysis, Processing and Understanding (MANPU 2017), 2017. [PDF]
• Criteria for Human-Compatible AI in Two-Player Vision-Language Tasks, C. Han†, S.-W. Lee†, Y.-J. Heo, W. Kang, J. Jun, and B.-T. Zhang, IJCAI 2017 Workshop on Linguistic and Cognitive Approaches to Dialog Agents (LaCATODA), 2017. (†Authors contributed equally) [PDF]
• Attention Memory for Locating an Object through Visual Dialogue, C. Han†, Y.-J. Heo†, W.-Y. Kang, J.-H. Jun, and B.-T. Zhang, CVPR 2017 Workshop on VQA Challenge, 2017. (†Authors contributed equally)
• Hadamard product for low-rank bilinear pooling, J.-H. Kim, K.-W. On, W. Lim, J. Kim, J.-W. Ha, B.-T. Zhang, The 5th International Conference on Learning Representations (ICLR), 2017. [PDF]
• Multi-focus attention network for efficient deep reinforcement learning, J. Choi, B.-J. Lee, and B.-T. Zhang, AAAI 2017 Workshop on What's next for AI in games (WNAIG 2017), 2017. [YouTube][PDF]

• Humans and machines in the evolution of AI in Korea, B.-T. Zhang, AI Magazine, 37(2):108-112, 2016. [PDF][Link]
• Whole-body balancing walk controller for position controlled humanoid robots, S.-J. Yi, B.-T. Zhang, D. W. Hong, and D. D. Lee, International Journal of Humanoid Robotics, 13(1):1550047, 2016. [PDF]
• Survey of computational haplotype determination methods for single individual, J.-K. Rhee, H. Li, J.-G. Joung, K.-B. Hwang, B.-T. Zhang,and S.-Y. Shin, Genes & Genomics, 38:1-12, 2016. [PDF]
• Special issue: First International Conference on Big Data and Smart Computing (BigComp2014), J. Kim, J. Kwok, K. Sumiya, B.-T. Zhang, Data & Knowledge Engineering, 104:15-16, 2016. [PDF]
• Multimodal residual learning for visual QA, J.-H. Kim, S.-W. Lee, D.-H. Kwak, M.-O. Heo, J. Kim, J.-W. Ha, and B.-T. Zhang, Advances in Neural Information Processing Systems 29 (NIPS 2016), 2016. [PDF]
• DeepSchema: Automatic schema acquisition from wearable sensor data in restaurant situations, E.-S. Kim, K.-W. On, and B.-T. Zhang, International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 834-840, 2016. [PDF]
• Dual-memory deep learning architectures for lifelong learning of everyday human behaviors, S.-W. Lee, C.-Y. Lee, D. H. Kwak, J. Kim, J. Kim, and B.-T. Zhang, International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 1669-1675, 2016. [PDF]
• Childbot: A conversational assistant for child care, H. Jo, W.-Y. Kang, D.-S. Han, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.91-92, 2016. [PDF] (poster)
• Storybot: Story learning from cartoon videos via consecutive event embedding, M.-O. Heo, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.87-88, 2016. [PDF] (poster)
• Pororobot: Child tutoring robot for English education, K. Kim, C. Nan, M.-O. Heo, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.85-86, 2016. [PDF] (poster) (Best Poster Award)
• Cafebot - A conversational cashier robot in cafes, C. Han, K.-W. On, E.-S. Kim, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.83-84, 2016. [PDF] (poster)
• Knowledgebot: Neuroknowledge based complimentary learning model for question answering systems, K.-W. On, E.-S. Kim, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.81-82, 2016. [PDF] (poster)
• Pandabot: Multimodal story learning with dynamic memory construction, Y.-J. Heo, E.-S. Kim,K.-W. On, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.79-80, 2016. [PDF] (poster)
• Jibobot: A personal assistant robot with social motions, E.-S. Kim, J. Kim, D.-H. Kwak,K.-W. On, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.77-78, 2016. [PDF] (poster)
• Glassbot: Personalized wearable agents learning from everyday human behaviors, S.-W. Lee, C.-Y. Lee, D.-H. Kwak, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.75-76, 2016. [PDF] (poster)
• Cambot: A visual conversation robot for interactive engagement, K. Kim, J.-H. Kim, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.73-74, 2016. [PDF] (poster)
• Schedulebot: A home robot learning and acting schedule adaptively via dynamic environments, C.-Y. Lee, S.-W. Lee, C. Lee, and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.69-70, 2016. [PDF] (poster)
• Aupair: A home robot for personal care, B.-J. Lee and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.67-68, 2016. [PDF] (poster)
• Visual imagination from texts, H. Kwak and B.-T. Zhang, 2016 International Symposium on Perception, Action, and Cognitive Systems: Beyond AlphaGo (PACS 2016), pp.44-45, 2016. [PDF] (poster)
• Molecular computation of multimodal pattern learning based on the hypernetwork model, H.-S. Chun and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 22), p.113, 2015. [PDF] (poster)
• Ways of conditioning generative adversarial networks, H. Kwak and B.-T. Zhang, NIPS 2016 Workshop on Generative Adversarial Networks, 2016. [PDF]
• PororoQA: Cartoon video series dataset for story understanding, K. Kim, C. Nan, M.-O. Heo, S.-H. Choi, and B.-T. Zhang, NIPS 2016 Workshop on Large Scale Computer Vision System, 2016.
• Generating images part by part with composite generative adversarial networks, H. Kwak, and B.-T. Zhang, IJCAI 2016 Workshop on Deep Learning for Artificial Intelligence (DLAI), 2016. [PDF]
• Sensory cue integration with high-order deep neural networks, K.-W. On, E.-S. Kim, and B.-T. Zhang, IJCAI 2016 Workshop on Closing the Cognitive Loop: Third Workshop on Knowledge, Data, and Systems for Cognitive Computing (CogComp 2016), 2016. [PDF]
• High-order deep neural networks for learning multi-modal representations, K.-W. On, E.-S. Kim, and B.-T. Zhang, ICML 2016 Workshop on Multi-View Representation Learning (MVRL), 2016. [PDF]
• Multimodal residual learning for visual question-answering, J.-H. Kim, S.-W. Lee, D.-H. Kwak, M.-O. Heo, J. Kim. J.-W. Ha, and B.-T. Zhang, CVPR 2016 Workshop on VQA Challenge, 2016. [PDF]
• Human body orientation estimation using convolutional neural network, J. Choi, B.-J. Lee, and B.-T. Zhang, IROS 2016 Workshop on Assistance and Service Robotics in a Human Environment, 2016. [arXiv]

• Molecular learning with DNA kernel machines, Y.-K. Noh, D.D. Lee, K.-A. Yang, C. Kim, and B.-T. Zhang, BioSystems, 137:73-83, 2015. [PDF]
• Team THOR's entry in the DARPA robotics challenge trials 2013, S.-J. Yi, S.G. McGill, L. Vadakedathu, Q. He, I. Ha, J. Han, H. Song, M. Rouleau, B.-T. Zhang, D. Hong, M. Yim, and D.D. Lee, Journal of Field Robotics, 32(3):315-335, 2015. [PDF]
• Consensus analysis and modeling of visual aesthetic perception, T.-S. Park and B.-T. Zhang, IEEE Transactions on Affective Computing, 6(3):272-285, 2015. [PDF]
• Characteristic molecular vibrations of adenosine receptor ligands, H. K. Chee, J.-S. Yang, J.-G. Joung, B.-T. Zhang, S. J. Oh, FEBS Letters, 589:548-552, 2015. [PDF]
• Editorial: Special issue on advanced intelligent system - Preface, J.-W. Jung, H. Wakuya, and B.-T. Zhang, Soft Computing, 19(4):813-814, 2015. [PDF]
• Modeling situated conversations for a child-care robot using wearable devices, K.-W. On, E.-S. Kim, and B.-T. Zhang, AAAI 2015 Fall Symposium on AI for Human-Robot Interaction (AI-HRI 2015), pp. 103-106, 2015. [PDF]
• Pororobot: A deep learning robot that plays video Q&A games, K.-M. Kim, C.-J. Nam, J.-W. Ha, Y.-J. Heo, and B.-T. Zhang, AAAI 2015 Fall Symposium on AI for Human-Robot Interaction (AI-HRI 2015), pp. 89-93, 2015. [PDF]
• Behavioral pattern modeling of human-human interaction for teaching restaurant service robots, E.-S. Kim, K.-O. On, and B.-T. Zhang, AAAI 2015 Fall Symposium on AI for Human-Robot Interaction (AI-HRI 2015), 2015. [PDF] (poster)
• Schedule management system for child-care home robot, D.-H. Kwak and B.-T. Zhang, AAAI 2015 Fall Symposium on AI for Human-Robot Interaction (AI-HRI 2015), 2015. [PDF] (poster)
• Neural network-based Bayesian optimization for efficient search of organic molecules, S. Yoon, H. Kwak, C. Han, M. Shim, and B.-T. Zhang, The 16th International Symposium on Advanced Intelligent Systems (ISIS 2015), 2015. (poster)(Best session paper awards) [PDF]
• An adaptive computational discourse system based on data-driven learning algorithm, S. Lee , J. Hwang, E. Kim, and B.-T. Zhang, The 16th International Symposium on Advanced Intelligent Systems (ISIS 2015), 2015. (poster)(Best session paper awards) [PDF]
• Analyzing human behavioral data to interact with restaurant server agents, E.-S. Kim, K.-W. On, and B.-T. Zhang, Third International Conference on Human-Agent Interaction (HAI 2015), p.333-336, 2015. [PDF] (Best poster award)
• Social network analysis of TV drama characters via deep concept hierarchies, C.-J. Nan, K.-M. Kim, and B.-T. Zhang, International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015), pp. 831-836, 2015. (oral presentation, accept ratio=18%, full paper) [PDF]
• Automated construction of visual-linguistic knowledge via concept learning from cartoon videos, J.-W. Ha, K.-M. Kim, and B.-T. Zhang,  In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 522-528, 2015. (oral presentation, accept ratio=12%) [PDF][Suppl]
• Dual memory architectures for fast deep learning of stream data via an online-incremental-transfer strategy, S.-W. Lee, M.-O. Heo, J. Kim, J. Kim, and B.-T. Zhang, ICML Workshop on Deep Learning, 2015. [PDF]
• DNA encodings for in vitro molecular learning of multimodal data, H.-S. Chun and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 21), p.112, 2015. [PDF] (poster, Trave Grant awarded)
• Molecular evolutionary learning of DNA Hypernetworks for hand-written digit classification, Christina Baek, J.-H. Ryu, J.-H. Lee and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 21), p.113, 2015. [PDF] (poster)
• Deep learning for the Web, Kyomin Jung, Byoung-Tak Zhang, Prasenjit Mitra, WWW 2015 (Companion Volume), 1526-1526, 2015. (Tutorial)
• Deep learning-based video analysis techniques, J. Kim, C.-J. Nan, and B.-T. Zhang, Communications of the Korean Institute of Information Scientists and Engineers, 33(9):21-31, 2015. [PDF] (in Korean)
• Deep hypernetwork models, B.-T. Zhang, Communications of the Korean Institute of Information Scientists and Engineers, 33(8):11-24, 2015. [PDF] (in Korean)

• Y.-Y. Choi and B.-T. Zhang, Communication: Human, animals, and artificial Intelligence (Korean translation of "Menschen, Tiere und Max: Natuerliche Kommunikation und kuenstliche Intelligenz" by I. Wachsmuth, Springer, 2012), Seoul National University Press, 2014.
• Bayesian evolutionary hypergraph learning for predicting cancer clinical outcomes, S.-J Kim, J.-W. Ha, and B.-T. Zhang, Journal of Biomedical Informatics,49:101-111, 2014. [PDF]
• The demand for quantitative techniques in biomedical image informatics, H.-Y. Jang, H.-R. Kim, M.-S. Kang, M.-H. Kim, and B.-T. Zhang, Biomedical Engineering Letters, 4(4):319-327, 2014. [PDF]
• Ontogenesis of agency in machines: A multidisciplinary review, B.-T. Zhang, AAAI 2014 Fall Symposium on The Nature of Humans and Machines: A Multidisciplinary Discourse, Arlington, VA, 2014. [PDF]
• Effective EEG connectivity analysis of episodic memory retrieval, C.-Y. Lee and B.-T. Zhang, In Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2014), pp. 833-838, 2014. [PDF]
• Predictive property of hidden representations in recurrent neural network language models, S. Yoon, S.-W. Lee, and B.-T. Zhang, 2014 NIPS workshop on Modern Machine Learning Methods and Natural Language Processing, 2014. [PDF]
• Uncovering response biases in recommendation, K.-W. Park, B.-H. Kim, T.-S. Park, and B.-T. Zhang, AAAI 2014 Multidisciplinary Workshop on Advances in Preference Handling (M-PREF), pp. 73-78, 2014. [PDF]
• Non-parametric Bayesian sum-product networks, S.-W. Lee, C. J. Watkins, B.-T. Zhang, ICML Workshop on Learning Tractable Probabilistic Models, 2014. [PDF]
• Use of symmetric internal loops for molecular pattern classification, J.-H. Lee, Christina Baek, H.-S. Chun, J.-H. Ryu,  R. Deaton, and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 20), p.90, 2014. [PDF] (poster, Trave Grant awarded)
• Molecular rewrite operation by mung bean nuclease, J.-H. Ryu, J.-H. Lee and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 20), p.89, 2014. [PDF] (poster, Trave Grant awarded)
• Molecular computation modeling of human anagram solving, H.-S. Chun, J.-H. Lee, J.-H. Ryu, Christina Baek, E.-S. Lee, and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 20), p.88, 2014. [PDF] (poster, Trave Grant awarded)
• Active long fixation correlates with the formation of long-term memory, J.-H. Kim and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 28, 2014. (poster)
• Analysis of information flow network during episodic memory retrieval, C.-Y. Lee and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 28, 2014. (poster)
• Recognizing visual images through latent graphica lmodels based on the Bayesian nonparametric methods, J. Yang and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 29, 2014. (poster)
• Emulating neural assemblies by molecular assemblies: Molecular computing simulation of digit recognition, J.-H. Ryu, H.-S. Chun, C. Baek, J.-H. Lee, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 30, 2014. (poster)
• Cognitive language learning with molecular associative memory, J.-H. Lee and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 31, 2014. (poster)
• Motor imaginary brain response classification using ensemble classification method, B. Hwang, C. Park, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 31, 2014. (poster)
• Active data selection scheme for deep neural network, S. Yoon, C. Han, H. Kwak, M. Shim, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 33, 2014. (poster)
• Sum-product graphical model and tree-augmented sum-product networks, S.-W. Lee and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 34, 2014. (poster)
• Incremental music learning with sparse ensemble codingfor regeneration, C. Han, B.-H. Kim, and B.-T. Zhang,  Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 35, 2014. (poster)
• RBIAS: A model of users' response biases in item ratings, K.-W. Park, B.-H. Kim, T.-S. Park, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 35, 2014. (poster)
• Restaurant environment customer's lifelong incremental action sequence learning self-motivated developmental cognitive robot, B.-J. Lee, C.-M. Choi, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 36, 2014. (poster)
• Closed-form approximation of drift diffusion response time for parameter estimation, J. Kim. Y.-K. Noh, M. Fific, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 37, 2014. (poster)
• Locally linear embedding for face recognition with simultaneous diagonalization, E.-S. Kim, Y.-K. Noh, M. Sugiyama, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 37, 2014. (poster)
• Representation learning for accelerometer data using convolutional deep belief network, K.-W. On and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 38, 2014. (poster)
• Multimodal hierarchical models for visually grounded concept learning from cartoon videos, K.-M. Kim, J.-W. Ha, B.-J. Lee, and B.-T. Zhang, Asia-Pacific Conference on Computational Behavioral Sciences (APCCBS 2014), p. 38, 2014. (poster)

• B.-T., Zhang, Communication as moving target tracking: Dynamic Bayesian inference with an action-perception-learning cycle, In  Wachsmuth, Ipke, Jan de Ruiter, Petra Jaecks and Stefan Kopp (eds.), Alignment in Communication. Towards a New Theory of Communication, Chapter 7, John Benjamins, 2013. [PDF]
• Biomolecular computation with molecular beacons for quantitative analysis of target nucleic acids, H.-W. Lim, S.H. Lee, K.-A. Yang, S-I. Yoo, T.H. Park, and B.-T. Zhang, Biosystems, 111(1):11-17, 2013. [PDF]
• Rule-based in vitro molecular classification and visualization, S.-Y. Shin, K.-A. Yang, I.-H. Lee, S.H. Lee. T.H. Park, and B.-T. Zhang, BioChip Journal, 7(1), 2013. [PDF]
• Constructing higher-order miRNA-mRNA interaction networks in prostate cancer via hypergraph-based learning, S.-J. Kim, J.-W. Ha, and B.-T. Zhang, BMC Systems Biology, 7:47, 2013. [PDF]
• Non-linear molecular pattern classification using molecular beacons with multiple targets, I.-H. Lee, S.H. Lee. T.H. Park, and B.-T. Zhang, BioSystems, 114(3):206-213, 2013. [PDF]
• Integrated analysis of genome-wide DNA methylation and gene expression profiles in molecular subtypes of breast cancer, J.-K. Rhee, K, Kim, H, Chae, J, Evans, P, Yan, B.-T. Zhang, J, Gray, P, Spellman, T, H.-M. Huang, K, P. Nephew, and S. Kim, Nucleic Acids Research, 41(18):8464-8474, 2013. [PDF]
• Construction of microRNA functional families by a mixture model of position weight matrices, J.-K. Rhee, S.-Y. Shin and B.-T. Zhang,  PeerJ, 1:e199, 2013. [PDF]
• Information-theoretic objective functions for lifelong learning, B.-T. Zhang, AAAI 2013 Spring Symposium on Lifelong Machine Learning, pp. 62-69, Stanford University, 2013. [PDF]
• Online learning of low dimensional strategies for high-level push recovery in bipedal humanoid robots, S.-J. Yi, B.-T. Zhang, D. Hong, and D. D. Lee, In Proceedings of IEEE International Conference on Robotics and Automation (ICRA 2013), pp. 1649-1655, 2013. [PDF]
• Estimating multiple evoked emotions from videos, W.H. Choe, H.-S. Chun, J. Noh, S.-D. Lee, and B.-T. Zhang, In Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2013), pp. 2046-2051, 2013. [PDF]
• Enhancing human action recognition through spatio-temporal feature learning and semantic rules,  K. Ramirez-Amaro, E.-S. Kim, J. Kim, B.-T. Zhang, M. Beetz and G. Cheng, In Proceedings of 2013 IEEE-RAS International Conference on Humanoid Robots (Humanoids 2013), 456-461, 2013.  [PDF] [Video]
• Evolutionary concept learning from cartoon videos by multimodal hypernetworks, B. J. Lee, J. W. Ha, K. M. Kim, and B. T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2013), pp. 1186-1192, 2013. [PDF]
• Learning global-to-local discrete components with nonparametric Bayesian feature construction, M.-O. Heo, S.-W. Lee, J. Lee, and B.-T. Zhang, 2013 NIPS workshop on Constructive Machine Learning, 2013. [PDF]
• Molecular computational simulation of cognitive processes for anagram solving, J.-H. Lee, E. S. Lee, J.-H. Ryu, H.-S. Chun and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 19), p.40, 2013. (poster) [PDF]
• Integrated encoding of semantic and orthographic distances in a DNA language model, J.-H. Ryu, J.-H. Lee and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 19), p.39, 2013. (poster) [PDF]
• Data driven SLAM for a mobile robot with short ranged navigation sensors, J. Lee, S.-H. Ji, and B.-T. Zhang, Proceedings of the 17th International Conference on Mechatronics Technology (ICMT 2013), pp. 377-379, 2013. [PDF]
• Dependable Escorting a VIP with collective robots in the unstructured environments, J. Lee, S.-H. Ji, and B.-T. Zhang, Proceedings of the 17th International Conference on Mechatronics Technology (ICMT 2013), pp. 380-382, 2013. [PDF]
• Online incremental structure learning of sum-product networks, S.-W. Lee, M.-O. Heo, and B.-T. Zhang, In Proceedings of the 20th International Conference on Neural Information Processing (ICONIP 2013), Lecture Notes in Computer Science, 8227:220-227, 2013. [PDF]
• Effects of model complexity on generalization performance of convolutional neural networks, T.-J. Kim, D. Zhang, and J.S. Kim, In Proceedings of the 14th International Symposium on Advanced Intelligent Systems (ISIS 2013), 2013. [PDF]
• Generating cafeteria conversations with a hypernetwork dialogue model, J.-H. Oh, H.-S. Chun, and B.-T. Zhang, In Proceedings of the 14th International Symposium on Advanced Intelligent Systems (ISIS 2013),  pp. 1424-1435, 2013. [PDF]
• Construction of microRNA functional families by a mixture model of position weight matrices, J.-K. Rhee, S.-Y. Shin and B.-T. Zhang, In Proceedings of the International Conference on Bioinformatics (InCoB2013), 2013.

• Biomolecular theorem proving on a chip: A novel microfluidic solution to a classical logic problem, S.H. Lee, D. van Noort, K.-A. Yang, I.-H. Lee, B.-T. Zhang, and T.H. Park, Lab on a Chip, 12(10):1841-1847, 2012. [PDF]
• A probabilistic coevolutionary biclustering algorithm for discovering coherent patterns in gene expression dataset, J.-G. Joung, S.-J. Kim, S.-Y. Shin and B.-T. Zhang, BMC Bioinformatics, 13(Suppl 17):S12, 2012. [PDF]
• Sparse population code models of word learning in concept drift, B.-T. Zhang, J.-W. Ha, and M. Kang, In Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2012), pp. 1221-1226, 2012. [PDF]
• Neural correlates of episodic memory formation in audio-visual pairing tasks, C.-Y. Lee, B.-J. Lee, J. S. Kim, and B.-T. Zhang, In Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2012), pp. 1864-1869, 2012 [PDF]
• Active stabilization of a humanoid robot for real-time imitation of a human operator, S.-J. Yi, S. McGill, B.-T. Zhang, D. Hong, and D.D. Lee, In Proceedings of 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012),  pp. 761-766, 2012. [PDF]
• Active stabilization of a humanoid robot for impact motions with unknown reaction forces, S.-J. Yi, B.-T. Zhang, D. Hong, and D. D. Lee, In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012), pp. 4034-4039, 2012. [PDF]
• Text-to-image retrieval based on incremental association via multimodal hypernetworks, J.-W. Ha, B.-J. Lee, and B.-T. Zhang, 2012 IEEE Conference on Systems, Man, and Cybernetics (IEEE SMC 2012), pp. 3239-3244, 2012. [PDF]
• Evolutionary particle filtering for sequential dependency learning from video data, J.H. Yoo, H.-S. Seok, and B.-T. Zhang, IEEE World Congress Computational Intelligence (WCCI-CEC 2012), pp. 559-566, 2012. [PDF]
• A probabilistic coevolutionary biclustering algorithm for discovering coherent patterns in gene expression dataset, J.-G. Joung, S.-J. Kim, S.-Y. Shin and B.-T. Zhang, In Proceedings of the International Conference on Bioinformatics (InCoB2012), BMC Bioinformatics, 13(Suppl 17):S12, 2012. [PDF]
• Molecular machine learning in vitro, J.-H. Lee, J.-W. Kim, R. Deaton, S. H. Lee, T. H. Park, and B.-T. Zhang, International Conference on DNA Computing and Molecular Programming (DNA 18), p.55, 2012. [PDF] (poster)
• Higher-order predictive information for learning an infinite stream of episodes, B.-T. Zhang, 2012 NIPS Workshop on Information in Perception and Action, 2012. (poster) [PDF]
• Place awareness learned by mobile vision-GPS sensor data, C.-Y. Lee, B.-J. Lee, J.-W. Ha, B.-T. Zhang, 2012 NIPS Workshop on Machine Learning Approaches to Mobile Context Awareness, 2012. (poster) [PDF]
• Learning-style recognition from eye-hand movement using a dynamic Bayesian network, E.-S. Kim, Y.-K. Noh, B.-T. Zhang, 2012 NIPS Workshop on Personalizing Education on Machine Learning, 2012. (poster) [PDF]
• Learning the dynamics of eye-hand movement in memory recall from videos, E.-S. Kim, B.-T. Zhang, Women in Machine Learning (WiML 2012), 2012. (poster) [PDF]
• EEG Analysis on Story Change in TV Drama, C.-Y. Lee, B.-J. Lee, and B.-T. Zhang, Proceedings of The 8th Asian-Pacific Conference on Vision (APCV 2012), p54, 2012.
• The relation of eye and hand movement during multimodal recall memory, E.-S. Kim, J. Kim, B.-T. Zhang, Proceedings of The 8th Asian-Pacific Conference on Vision (APCV 2012), p40, 2012.
• Hierarchical slow-feature models of gesture conversation, J. Kim, S. Jang, E.-S. Kim, B.-T. Zhang, Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2012), p. 2722, 2012. (poster) [PDF]
• 'Is this right?' or 'Is that wrong?': Evidence from dynamic eye-hand movement in decision making, E.-S. Kim, J. Kim, T. Pfeiffer, I. Wachsmuth, and B.-T. Zhang, Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2012), p. 2723, 2012. (poster) [PDF]
• Complex network analysis of social relationships and personality from TV drama dialogues, J.S. Kim, C.-Y. Lee, M. Zhang. and J.-H. Nam, Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2012), p. 2726, 2012.  (poster) [PDF]
• Effect of saliency-based masking in scene classification, T.-S. Park and B.-T. Zhang, Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2012), p. 2839, 2012. (poster) [PDF]

• Feature relevance network-based transfer learning for indoor location estimation, H.-S. Seok,  K.-B. Hwang, and B.-T. Zhang, IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, 41(5):711-719, 2011.   [PDF]
• A DNA assembly model of sentence generation, J.-H. Lee, S. H. Lee, W.-H. Chung, E. S. Lee, T. H. Park, R. Deaton, and B.-T. Zhang, BioSystems, 106:51-56, 2011. [PDF]
• Ensemble learning with active example selection for imbalanced biomedical data classification, S. Oh, M.S. Lee, and B.-T. Zhang, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8(2):316-325, 2011. [PDF]
• Practical bipedal walking control on uneven terrain using surface learning and push recovery, S.-J. Yi, B.-T. Zhang, D. Hong, and D. D. Lee, In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), pp. 3963-3968, 2011. [PDF]
• Online learning of a full body push recovery controller for omnidirectional walking, S. J. Yi, B.-T. Zhang, D. Hong, and D. D. Lee, In Proceedings of 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2011), pp. 1-6, 2011. [PDF]
• Learning full body push recovery control for small humanoid robots, S. J. Yi, B.-T. Zhang, D. Hong, and D. D. Lee, In Proceedings of IEEE International Conference on Robotics and Automation (ICRA 2011), pp. 2047-2052, 2011. [PDF]
• Identifying functional miRNA-mRNA modules based on hypergraph-based learning, S.-J. Kim, J.-W. Ha, and B.-T. Zhang, IEEE International Student Paper Contest - Seoul Section, pp. 73-78, 2011. (Gold Prize Award)
• Mutual information-based evolution of hypernetworks for brain data analysis, E.-S. Kim, J.-W. Ha, W.H. Jung, J.H. Jang, J.S. Kwon, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2011), pp. 2721-2727, 2011. [PDF]
• Evolving a population code for multimodal concept learning, B. Lee, H.-S. Seok, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2011), pp. 809-816, 2011. [PDF]
• A molecular evolutionary algorithm for learning hypernetworks on simulated DNA computers, J.-H. Lee, B. Lee, J.S. Kim, R. Deaton, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2011), pp. 2845-2852, 2011. [PDF]
• Bayesian mixture modeling of joint vision-language concepts from videos, B.-T. Zhang, M.-G. Kang, 2011 NIPS Workshop on Integrating Language and Vision, (poster), 2011.
• Slice sampling in nested IBP, J. Yang, J. Nam, B.-T. Zhang, 2011 NIPS Workshop on Bayesian Nonparametrics: Hope or Hype?, (poster), 2011. [PDF]
• Video streams semantic segmentation utilizing multiple channels with different time granularity, B. Lee, H.-S. Seok, and B.-T. Zhang, 2011 NIPS Workshop on Bayesian Nonparametrics: Hope or Hype?, (poster), 2011.
• Text-to-image generation based on crossmodal association with hierarchical hypergraphs, J.-W. Ha and B.-T. Zhang, 2011 NIPS Workshop on Integrating Vision and Language, (poster), 2011. [PDF]
• Identifying functional miRNA-mRNA modules based on hypergraph-based learning, S.-J. Kim, J.-W. Ha, and B.-T. Zhang, 2011 NIPS Workshop on Machine Learning in Computational Biology (MLCB 2011), (poster), 2011. [PDF]
• Modeling situated language learning in early childhood via hypernetworks, B.-T. Zhang, E.-S. Lee, M.-O. Heo, and M.-G. Kang, Embodied & Situated Language Processing (ESLP 2011), p.48, (poster), 2011. [PDF]
• Interaction of language and vision memories in TV drama watching: An EEG study, C.-Y. Lee, E.-S. Kim, J.-S. Kim, and B.-T. Zhang, Embodied & Situated Language Processing (ESLP 2011), p.49, (poster), 2011. [PDF]
• Deciphering the communicative code in speech and gesture dialogues by autoencoding hypernetworks, J.-S. Nam, K. Bergmann, U. Waltinger, S. Kopp, I. Wachsmuth, B.-T. Zhang, Embodied & Situated Language Processing (ESLP 2011), p.15, (oral), 2011. [PDF]
• In vitro molecular learning of a DNA hypernetwork, J.-H. Lee, S.H. Lee, R. Deaton, T.H. Park, B.-T. Zhang, 17th International Conference on DNA Computing and Molecular Programming (DNA 17), pp. 46, (poster), 2011.
• Evolutionary hypernetworks based on mutual information for cancer gene expression profile analysis, S.-J. Kim, J.-W. Ha, and B.-T. Zhang, In Proceedings of the Ninth Asia-Pacific Bioinformatics Conference (APBC 2011), p. 286 (poster), 2011.
• Finding significant cortical modules on IQ by evolving region-based hypernetworks with mutual information, E.-S.Kim, J.-W. Ha, W. H. Jung, J. S. Kwon, and B.-T. Zhang, In Proceedings of the Ninth Asia-Pacific Bioinformatics Conference (APBC 2011), p. 288 (poster), 2011.
• Designing of DNA hypernetworks for molecular learning model, J.-H. Lee, S. H. Lee, T. H. Park, and B.-T. Zhang, In Proceedings of the Ninth Asia-Pacific Bioinformatics Conference (APBC 2011), p. 298 (poster), 2011.
• Identifying association of multiple single nucleotide polymorphisms loci with type2 diabetes, W. Yoon, J.-K. Rhee, J.-H. Lee, and B.-T. Zhang, In Proceedings of the Ninth Asia-Pacific Bioinformatics Conference (APBC 2011), p. 299 (poster), 2011.
• Construction of microRNA functional families by a mixture model of position weight matrices, J.-K. Rhee and B.-T. Zhang, In Proceedings of the Ninth Asia-Pacific Bioinformatics Conference (APBC 2011), p. 300 (poster), 2011.

• PRICAI 2010: Trends in Artificial Intelligence, 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings,B.-T. Zhang and M. A. Orgun (Eds.), Springer, 2010.
• Fluid dynamics models for low rank discriminant analysis, Y.-K. Noh, B.-T. Zhang, and D.D. Lee, Journal of Machine Learning Research - Proceedings Track, 9:565-572, 2010. [PDF]
• In vitro molecular pattern classification via DNA-based weighted sum operation, H.-W. Lim, S.H. Lee, K.-A. Yang, J.Y. Lee, S.-I. Yoo, T. H. Park, and B.-T. Zhang, BioSystems, 100(1):1-7, 2010. [PDF]
• Generative local metric learning for nearest neighbor classification, Y.-K. Noh, B.-T. Zhang, and D.-D. Lee, In Advances in Neural Information Processing Systems 24 (NIPS 2010), pp. 1822-1830, 2010. [PDF]
• Layered hypernetwork models for cross-modal associative text and image keyword generation in multimodal information retrieval, J.-W. Ha, B.-H. Kim, B. Lee, and B.-T. Zhang, Proceedings of the Eleventh Pacific Rim International Conference on AI (PRICAI2010), Lecture Notes in Artificial Intelligence, 6230:76-87, 2010. [PDF]
• Visual query expansion via incremental hypernetwork models of image and text, M.-O. Heo, M.-G. Kang, and B.-T. Zhang, Proceedings of the Eleventh Pacific Rim International Conference on AI (PRICAI2010), Lecture Notes in Artificial Intelligence, 6230:88-99, 2010. [PDF]
• MMG: A learning game platform for understanding and predicting human recall memory, U. Fareed and B.-T. Zhang, The 11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010), Lecture Notes in Artificial Intelligence, 6232:300-309, 2010. [PDF]
• Subjective document classification using network analysis, M. Kim, B.-T. Zhang, and J.-S. Lee, International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2010), pp. 365-369, 2010.
• Evolutionary layered hypernetworks for identifying microRNA-mRNA regulatory modules, S.-J. Kim, J.-W. Ha, B. Lee, and B.-T. Zhang, IEEE World Congress Computational Intelligence (WCCI-CEC 2010), pp. 2299-2306, 2010. [PDF]
• Online learning of uneven terrain for humanoid bipedal walking, S.-J. Yi, B.-T. Zhang, and D.-D. Lee, AAAI Conference on Artificial Intelligence (AAAI 2010), pp. 1639-1644, 2010.   [PDF]
• Fluid dynamics models for low rank discriminant analysis, Y.-K. Noh, B.-T. Zhang, and D.-D. Lee, Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010), pp. 565-572, 2010.   [PDF]

• Intelligent and Evolutionary Systems, Gen, M., Green, D., Katai, O., McKay, B., Zhang, B.-T., Namatame, A., Sarker, R.A. (Eds.), Springer-Verlag, 2009.
• Identification of cell cycle-related regulatory motifs using a kernel canonical correlation analysis, J.-K. Rhee, J.-G. Joung, J.-H. Chang, Z. Fei and B.-T. Zhang, BMC Genomics, 10(Suppl 3):S29, 2009. [PDF]
• EvoOligo: Oligonucleotide probe design with multiobjective evolutionary algorithms, S.-Y. Shin, I.-H. Lee, Y.-M. Cho, K.-A. Yang, and B.-T. Zhang, IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 39(6):1606-1616, 2009. [PDF]
• Ensembled support vector machines for human papillomavirus risk type prediction from protein secondary structures, S. Kim, J. Kim, and B.-T. Zhang, Computers in Biology and Medicine, 39(2):187-193, 2009. [PDF]
• Effective mixing in a microfluidic chip using magnetic particles, S.-W. Lee, D. van Noort, J.-Y. Lee, B.-T. Zhang, T.-H. Park, Lab on a Chip, 9:479-482, 2009. [PDF]
• Teaching an agent by playing a multimodal memory game: challenges for machine learners and human teachers, B.-T. Zhang, AAAI 2009 Spring Symposium: Agents that Learn from Human Teachers, pp. 144-149, 2009. [PDF]
• Ensemble learning based on active example selection for solving imbalanced data problem in biomedical data, M.S. Lee, S. Oh, and B.-T. Zhang, IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2009), pp.350-355, 2009. [PDF]
• Dynamic and static influence models on starbucks networks, M. Kim, B.-T. Zhang, and J.-S Lee, International Conference on Advances in Social Network Analysis and Mining (ASONAM 2009), pp.344-347, 2009. [PDF]
• Social influence models based on starbucks networks, M. Kim, B.-T. Zhang, and J.-S Lee, International Conference on Computational Aspects of Social Networks (CASoN 2009), pp.3-9, 2009. [PDF]
• Evolving hypernetwork models of binary time series for forecasting price movements on stock markets, E. Bautu, S. Kim, A. Bautu, H. Luchian, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2009), pp.166-173, 2009. [PDF]
• An in vitro DNA hypernetwork for digit pattern recognition, K.-A. Yang, I.-H. Lee, and B.-T. Zhang, Preliminary Proceedings of the 15th International Meeting on DNA Computing (DNA15), 2009. [PDF]
• AESNB: active example selection with naive bayes classifier for learning from imbalanced biomedical data, M.S. Lee, J.-K. Rhee, B.-H. Kim, and B.-T. Zhang, IEEE Ninth International Conference on Bioinformatics & BioEngineering (BIBE 2009), pp.15-21, 2009. [PDF]
• Evolutionary hypernetwork classifiers for protein-protein interaction sentence filtering, J. Bootkrajang, S. Kim, and B.-T. Zhang, The Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 185-191, 2009. [PDF]
• Gender classification with cortical thickness measurement, J.-W. Ha, J.H. Jang, D.-H. Kang, W.H. Jung, J.S. Kwon, and B.-T. Zhang, IEEE International Conference on Fuzzy Systems (Fuzz IEEE 2009), pp. 41-46, 2009. [PDF]
• Evolutionary hypernetworks for learning to generate music from examples, H.-W. Kim, B.-H. Kim, and B.-T. Zhang, IEEE International Conference on Fuzzy Systems (Fuzz IEEE 2009), pp. 47-52, 2009. [PDF]
• Text-to-image cross-modal retrieval of magazine articles based on higher-order pattern recall by hypernetworks, J.-W. Ha, B.-H. Kim, H.-W. Kim, W.C. Yoon, J.-H. Eom, and B.-T. Zhang, The 10th International Symposium on Advanced Intelligent Systems (ISIS 2009), pp. 274-277, 2009. [PDF] (Best paper awarded)
• Kernel machines made of DNA molecules, Y.-K. Noh, D.D. Lee, C. Kim, and B.-T. Zhang, Learning Workshop (Snowbird Workshop), 2009. [PDF]

• Evolutionary multiobjective optimization for DNA sequence design, S.-Y. Shin, I.-H. Lee, B.-T. Zhang, Multi-Objective Optimization in Computational Intelligence: Theory and Practice, Chapter 9, Information Science Reference, 2008.
• Supervised learning methods for microRNA studies, B.-T. Zhang and J.-W. Nam, Machine Learning in Bioinformatics, Chapter 16, John Wiley & Sons, 2008.
• Hypernetworks: A molecular evolutionary architecture for cognitive learning and memory, B.-T. Zhang, IEEE Computational Intelligence Magazine, 3(3):49-63, 2008. [PDF] [LINK]
• The use of gold nanoparticle aggregation for DNA computing and logic-based biomolecular detection, I.-H. Lee, K.-A. Yang, J.-H. Lee, J.-Y. Park, Y. G. Chai, J.-H. Lee, and B.-T. Zhang, Nanotechnology, 19:395103, 2008. [PDF]
• Introducing meta-services for biomedical information extraction, F. Leitner, M. Krallinger, C. Rodriguez-Penagos, J. Hakenberg, C. Plake, C.-J. Kuo, C.-N. Hsu, R. T. Tasi, H.-C. Hung, W. W. lau, C. A. Johnson, R. Satre, K. Yoshida, Y. H. Chen, S. Kim, S.-Y. Shin, B.-T. Zhang, W. A. Baumgartner, Jr., L. Hunter, B. Haddow, M. Matthews, X. Wang, P. Ruch, F. Ehrler, A. Ozgur, G. Erkan, D. R. Radev, M. Krauthammer, T. Luong, R. Hoffmann, C. Sander, and A. Valencia, Genome Biology, 9(suppl 2):S6, 2008. [PDF]
• Characterization of biological effect of 1763 MHz radiofrequency exposure on auditory hair cells, T.-Q. Huang, M.S. Lee, E. Oh, F. Kalinec, B.-T. Zhang, J.-S. Seo, W.-Y. Park, International Journal of Radiation Biology, 84(11):909-915, 2008. [PDF]
• Molecular responses of Jurkat T-cells to 1763 MHz radiofrequency radiation, T.-Q. Huang, M.S. Lee, E. Oh, B.-T. Zhang, J.-S. Seo, W.-Y. Park, International Journal of Radiation Biology, 84(9):734-741, 2008. [PDF]
• PIE: An online prediction system for protein-protein interactions from text, S. Kim, S.-Y. Shin, I.-H. Lee, S.-J. Kim, R. Sriram, and B.-T. Zhang, Nucleic Acids Research, 35:W411-W415, 2008. [PDF]
• AptaCDSS-E: A classifier ensemble-based clinical decision support system for cardiovascular disease level prediction, J.-H. Eom, S.C. Kim, and B.-T. Zhang, Expert Systems with Applications, 34(4):2465-2479, 2008. [PDF]
• An evolutionary Monte Carlo algorithm for predicting DNA hybridization, J.-S. Kim, J.-W. Lee, Y.-K. Noh, J.-Y. Park, D.-Y. Lee, K.-A. Yang, Y.G. Chai, J.-C. Kim, and B.-T. Zhang, BioSystems, 91(1):69-75, 2008. [PDF]
• Cognitive learning and the multimodal memory game: Toward human-level machine learning, B.-T. Zhang, IEEE International Joint Conference on Neural Networks (IJCNN2008), pp. 3261-3267, 2008. [PDF]
• Self-assemblying hypernetworks for cognitive learning of linguistic memory, B.-T. Zhang and C.-H. Park, Proceedings of International Conference on Computer, Electrical, and Systems Science, and Engineering (CESSE2008)(WASET), Vol. 27, pp.134-138, 2008. [PDF]
• Weighted sum computation in vitro using differentially labeled molecular beacon, S.H. Lee, H.-W. Lim, K.-A. Yang, S.I. Yoo, B.-T. Zhang, T.H. Park, Preliminary Proceedings of the 14th International Meeting on DNA Computing (DNA14), p.16, 2008. [PDF]
• Modeling of RNAi-based NOR gates from gene expression data, K.-A. Yang, J.H. Lee, B.-T. Zhang, Preliminary Proceedings of the 14th International Meeting on DNA Computing (DNA14), p.205, 2008. [-]

• A global minimization algorithm based on a geodesic of a Lagrangian formulation of Newtonian dynamics, J.-S. Kim, J.-C. Kim, J.-M. O, and B.-T. Zhang, Neural Processing Letters, 26(2):121-131, 2007. [PDF]
• Discovery of microRNA-mRNA modules via population-based probabilistic learning, J.-G. Joung, K.-B. Hwang, J.-W. Nam, S.-J. Kim and B.-T. Zhang, Bioinformatics, 23(9):1141-1147, 2007. [PDF]
• Identification and characterization of small RNAs from vernalized Arabidopsis thaliana, Oh, M., Lee, H., Kim, Y.-K., Nam, J.-W., Rhee, J.-K., Zhang, B.-T., Kim, V.N., Lee, I., Journal of Plant Biology, 50(5):562-572, 2007. [PDF]
• Finding cancer-related gene combinations using a molecular evolutionary algorithm, C.-H. Park, S.-J. Kim, S. Kim, D.-Y. Cho, and B.-T. Zhang, IEEE 7th international conference on Bioinformatics & BioEngineering (BIBE 2007), pp. 158-163, 2007 . [PDF]
• Evolving hypernetworks for pattern classification, J.-K. Kim and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2007), pp.1856~1862, 2007 . [PDF]
• Evolving hypernetwork classifiers for microRNA expression profile analysis, S. Kim, S.-J. Kim, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2007), pp. 313-319, 2007 . [PDF]
• Theoretical property of topological efficiency measurements for Markov decision problems, S.-J. Yi and B.-T. Zhang, 8th International Symposium on Advanced Intelligent Systems (ISIS 2007), pp. 699-701, 2007. [PDF]
• Use of evolutionary hypernetworks for mining prostate cancer data, C.-H. Park, S.-J. Kim, S. Kim, D.-Y. Cho, and B.-T. Zhang, 8th International Symposium on Advanced Intelligent Systems (ISIS 2007), pp. 702-706, 2007. [PDF]
• Random hypergraph models of learning and memory in biomolecular networks: shorter-term adaptability vs. longer-term persistency, B.-T. Zhang, The First IEEE Symp. on Foundations of Computational Intelligence (FOCI '07), pp. 344-349, 2007 .[PDF]
• Evolutionary hypernetwork models for aptamer-based cardiovascular disease diagnosis, J.-W. Ha, J.-H. Eom, S.-C. Kim, and B.-T. Zhang, The Genetic and Evolutionary Computation Conference (GECCO 2007), pp. 2709-2716, 2007 . [PDF]
• Identifying protein-protein interaction sentences using boosting and kernel methods, S.-Y. Shin, S. Kim, J.-H. Eom, B.-T. Zhang, and R. Sriram, Second BioCreative Challenge Workshop, pp. 187-192, 2007 . [PDF]
• Dinucleotide step parameterization of pre-miRNAs using multi-objective evolutionary algorithms, J.-W. Nam, I.-H. Lee, K.-B. Hwang, S.-B. Park, and B.-T. Zhang, Lecture Notes in Computer Science, EvoBio 2007, 4447:176-186, 2007. [PDF]
• A DNA computing-inspired silicon chip for pattern recognition, J.-K. Kim, B.S. Kim, O.H. Kwon, S.K. Hwang, J.-W. Ha, C.-H. Park, D.J. Chung, C.H. Lee, J. Park, and B.-T. Zhang, Preliminary Proceedings of the 13th International Meeting on DNA Computing (DNA13), p.373, 2007. [PDF]
• In vitro molecular pattern classification using DNA-based weighted sum computation, H.-W. Lim, S. H. Lee, K. A. Yang, S.-I. Yoo, T. H. Park, and B.-T. Zhang, Preliminary Proceedings of the 13th International Meeting on DNA Computing (DNA13), p.90, 2007. [PDF]
• Multiplex PCR assay design by hybrid multiobjective evolutionary algorithm, I.-H. Lee, S.-Y. Shin, B.-T. Zhang, Lecture Notes in Computer Science, EMO 2007, 4403:376-385, 2007. [PDF]
• Implementation of DNA computing for decision tree based disease classification, K.A. Yang, S.-Y. Shin, I.-H. Lee, J.-H. Lee, B.-T. Zhang, 2007 International Nanotech Symposium & Exhibition in Korea (NanoKorea 2007), p. 216, 2007.
• A multiple microRNA detection system based on computational self-assembly of DNA-gold nanoparticles, K.A. Yang , J.-H. Lee, I.-H. Lee, and B.-T. Zhang, Foundation of Nanoscience (FNANO 2007), p. 67, 2007.

• Combining information-based supervised and unsupervised feature selection, Sang-Kyun Lee, Seung-Joon Yi, Byoung-Tak Zhang, Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing), Chapter 24, Springer-Verlag, 2006.
• Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex, J. Han, Y. Lee, K.H. Yeom, J.-W. Nam, I. Heo, J.-K. Rhee, S. Y. Sohn, Y. Cho, B.-T. Zhang and V.N. Kim, Cell, 125:887-901, 2006. [PDF]
• ProMiR II: A web server for the probabilistic prediction of clustered, nonclustered, conserved and nonconserved microRNAs, J.-W. Nam, J.-H. Kim, S.-K. Kim, B.-T. Zhang, Nucleic Acids Research, 34:W455-W458, 2006. [PDF]
• miTarget: microRNA target-gene prediction using a Support Vector Machine, S.-K. Kim, J.-W. Nam, J.-K. Rhee, W.-J. Lee and B.-T. Zhang, BMC Bioinformatics, 7(1):411, 2006. [PDF]
• Identification of regulatory modules by co-clustering latent variable models: stem cell differentiation, J.-G. Joung, D. Shin, R. H. Seong, and B.-T. Zhang, Bioinformatics, 22(16):2005-2011, 2006. [PDF]
• Identification of biochemical networks by S-tree based genetic programming, D.-Y. Cho, K.-H. Cho, B.-T. Zhang, Bioinformatics, 22(13):1631-1640, 2006. [PDF]
• Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks, S. J. Oh, J.-G, Joung, J.-H. Chang, and B.-T. Zhang, BMC Bioinformatics, 7:284, 2006. [PDF]
• DNA hypernetworks for information storage and retrieval, B.-T. Zhang and J.-K. Kim, Lecture Notes in Computer Science, DNA 12, 4287:298-307, 2006. [PDF]
• Molecular learning of wDNF formulae, B.-T. Zhang and H.-Y. Jang, Lecture Notes in Computer Science, DNA 11, 3892:427-437, 2006. [PDF]
• Protein sequence-based risk classification for human papillomaviruses, J.-G. Joung, S. J. O, and B.-T. Zhang, Computers in Biology and Medicine, 36:656-667, 2006. [PDF]
• Simulation and real-time monitoring of polymerase chain reaction for its higher efficiency, Ji Youn Lee, Hee-Woong Lim, Suk-In Yoo, Byoung-Tak Zhang, and Tai Hyun Park, Biochemical Engineering Journal, 29:109-118, 2006. [PDF]
• Learning hierarchical Bayesian networks for large-scale data analysis, K.-B. Hwang, B.-H. Kim, and B.-T. Zhang, Lecture Notes in Computer Science, ICONIP 2006, 4232:670-679, 2006. [PDF]
• Microarray probe design using ε-multi-objective evolutionary algorithms with thermodynamic criteria, S.-Y. Shin, I.-H. Lee, and B.-T. Zhang, Lecture Notes in Computer Science, EvoBio 2006, 3907:184-195, 2006. [PDF]
• Human papillomavirus risk type classification from protein sequences using support vector machines, S. Kim and B.-T. Zhang, Lecture Notes in Computer Science, EvoBio 2006, 3907:57-66, 2006. [PDF]
• Multi-stage evolutionary algorithms for efficient identification of gene regulatory networks, K.-Y. Kim, D.-Y. Cho, and B.-T. Zhang, Lecture Notes in Computer Science, EvoBio 2006, 3907:45-56, 2006. [PDF]
• A tree kernel-based method for protein-protein interaction mining from biomedical literature, J.-H. Eom, S. Kim, S.-H. Kim, and B.-T. Zhang, Lecture Notes in Computer Science, KDLL 2006, 3886:42-52, 2006. [PDF]
• Mining protein interaction from biomedical literature with relation kernel method, J.-H. Eom and B.-T. Zhang, Lecture Notes in Computer Science, ISNN 2006, 3973:642-647, 2006. [PDF]
• Prediction of protein interaction with neural network-based feature association rule mining, J.-H. Eom and B.-T. Zhang, Lecture Notes in Computer Science, ICONIP 2006, 4234:30-39, 2006. [PDF]
• Adaptive stock trading with dynamic asset allocation using reinforcement learning, O, J., Lee, J., Lee, J. W., and Zhang, B.-T., Information Sciences, 176(15):2121-2147, 2006. [PDF]
• DNA hypernetworks for information storage and retrieval, B.-T. Zhang and J.-K. Kim, Preliminary Proceedings of the Twelfth International Meeting on DNA Computing (DNA 12), pp. 283-292, 2006. [PDF]
• Text classifiers evolved on a simulated DNA computer, S. Kim, M.-O. Heo, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2006), pp. 9196-9202, 2006. [PDF]
• Co-evolutionary biclustering for miRNA expression profiles analysis, S.-J. Kim, J.-G, Joung, and B.-T. Zhang, The 7th International Conference of Korean Society for Bioinformatics (BIOINFO 2006), pp. 60-65, 2006. [PDF]
• Massively parallel logical computation by self-Assembly of DNA-linked nanoparticles, Lee, I.H., Lee, J.-H., Yang, K.A., Lee, J. H., Chai, Y.-G., Zhang, B.-T., 2006 International Nanotech Symposium & Exhibition in Korea (NanoKorea 2006), p. 337, 2006.
• Evolutionary multiple-objective optimization of oligonucleotide probes, Shin, S.-Y., Cho, Y.-M., Lee, I.-H., Yang, K.A., Lee, J.-H., Zhang, B.-T., The 7th International Conference of Korean Society for Bioinformatics (BIOINFO 2006), p. 201, 2006.

• A Bayesian algorithm for in vitro molecular evolution of pattern classifiers, B.-T. Zhang and H.-Y. Jang, Lecture Notes in Computer Science, 3384:458-467, 2005. [PDF]
• Crosschip: a system supporting comparative analysis of different generations of Affymetrix arrays, Kong, S. W., Hwang, K.-B., Kim, R. D., Zhang, B.-T., Greenberg, S. A., Kohane, I. S., and Park, P. J., Bioinformatics, 21(9):2116-2117, 2005. [PDF]
• Multi-objective evolutionary optimization of DNA sequences for reliable DNA computing, S.-Y. Shin, I.-H. Lee, D. Kim and B.-T. Zhang, IEEE Transactions on Evolutionary Computation, 9(2):143-158, 2005. [PDF]
• Human microRNA prediction through a probabilistic co-learning model of sequence and structure, Jin-Wu Nam, Ki-Roo Shin, Jinju Han, Yoontae Lee, V. Narry Kim, and Byoung-Tak Zhang, Nucleic Acids Research, 33(11):3570-3581, 2005. [PDF]
• Bayesian model averaging of Bayesian network classifiers over multiple node-orders: application to sparse datasets, K.-B. Hwang and B.-T. Zhang, IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 35(6):1302-1310, 2005. [PDF]
• Bayesian network learning with feature abstraction for gene-drug dependency analysis, J.-H. Chang, K.-B. Hwang, S. J. O, and B.-T. Zhang, Journal of Bioinformatics and Computational Biology, 3(1):61-77, 2005. [PDF]
• Efficient initial pool generation for weighted graph problems using parallel overlap assembly, Ji Youn Lee, Hee-Woong Lim, Suk-In Yoo, Tai Hyun Park, and Byoung-Tak Zhang, Lecture Notes in Computer Science, DNA10, 3384:215-223, 2005. [PDF]
• Prediction of yeast protein-protein interactions by neural feature association rule, Jae-Hong Eom and Byoung-Tak Zhang, Lecture Notes in Computer Science, ICANN 2005, 3697:491-496, 2005. [PDF]
• Extraction of gene/protein interaction from text documents with relation kernel, Jae-Hong Eom and Byoung-Tak Zhang, Lecture Notes in Artificial Intelligence, KES 2005, 3682:936-942, 2005. [PDF]
• Dynamic asset allocation for stock trading optimized by evolutionary computation, Jangmin O, Jongwoo Lee, Jae Won Lee, and Byoung-Tak Zhang, IEICE Transactions on Information and Systems, E88-D(6):1217-1223, 2005. [PDF]
• Identification of Caenorhabditis elegans microRNA targets using a kernel method, W.-J. Lee, J.-W. Nam, S.-K. Kim, and B.-T. Zhang, Genomics & Informatics, 3(1):15-23, 2005. [PDF]
• A Kernel method for microRNA target prediction using sensible data and position-based features, S.-K. Kim, J.-W. Nam, W.-J. Lee, and B.-T. Zhang, IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2005), pp. 46-52, 2005. [PDF]
• Correlation analysis between regulatory sequence motifs and expression profiles by kernel CCA, J.-K. Rhee, J.-G. Joung, J.-H. Chang, and B.-T. Zhang, Proceedings of the 2005 International Joint Conference of InCoB, AASBi and KSBI (BIOINFO 2005), pp. 63-68, 2005. [PDF]
• Molecular programming: evolving genetic programs in a test tube, B.-T. Zhang and H.-Y. Jang, The Genetic and Evolutionary Computation Conference (GECCO 2005), vol. 2, pp. 1761-1768, 2005. [PDF]
• Molecular learning of wDNF formulae, B.-T. Zhang and H.-Y. Jang Preliminary Proceedings of the Eleventh International Meeting on DNA Computing (DNA 11), pp. 185-195, 2005. [PDF]
• Computerized simulation and experimental analysis for efficient polymerase chain reaction, H.-W. Lim, J. Y. Lee, S.-I. Yoo, B.-T. Zhang, and T. H. Park, Preliminary Proceedings of the Eleventh International Meeting on DNA Computing (DNA 11), p. 402, 2005. [PDF]
• Small world network based world representation for scalable reinforcement learning, S.-J. Yi and B.-T. Zhang, in Proceedings of the ICML'05 Workshop on Rich Representations for Reinforcement Learning, 2005. [PDF]

• Solving traveling salesman problems with DNA molecules encoding numerical values, J. Y. Lee, S.-Y. Shin, T. H. Park, and B.-T. Zhang, BioSystems, 78:39-47, 2004. [PDF]
• Co-trained support vector machines for large scale unstructured document classification using unlabeled data and syntactic information, S.-B. Park and B.-T. Zhang, Information Processing and Management, 40(3):421-439, 2004. [PDF]
• Development, evaluation and benchmarking of simulation software for biomolecule-based computing, Derrel Blain and Max Garzon, Soo-Yong Shin and Byoung-Tak Zhang, Satoshi Kashiwamura, Masahito Yamamoto, Atsushi Kameda, and Azuma Ohuchi, Natural Computing, 3(4):427-442, 2004. [PDF]
• PubMiner: machine learning-based text mining system for biomedical information analysis, J.-H. Eom and B.-T. Zhang, Genomics & Informatics, 2(2):99-106, 2004. [PDF]
• Genetic mining of DNA sequence structures for effective classification of the risk types of human papillomavirus(HPV), J.-H. Eom, S.-B. Park, and B.-T. Zhang, Lecture Notes in Computer Science, ICONIP 2004, 3316:1334-1343, 2004. [PDF]
• Searching transcriptional modules using evolutionary algorithms, J.-G. Joung, S. J. Oh, and B.-T. Zhang, Lecture Notes in Computer Science, PPSN 8, 3242:532-540, 2004. [PDF]
• Evolutionary continuous optimization by distribution estimation with variational Bayesian independent component analyzers mixture model, D.-Y. Cho and B.-T. Zhang, Lecture Notes in Computer Science, PPSN 8, 3242:212-221, 2004. [PDF]
• Dynamic asset allocation exploiting predictors in reinforcement learning framework, J. O, J. W. Lee, J.-W. Lee, and B.-T. Zhang, Lecture Notes in Artificial Intelligence, ECML/PKDD 2004, 3201:298-309, 2004. [PDF]
• PubMiner: machine learning-based text mining system for biomedical information mining, J.-H. Eom and B.-T. Zhang, Lecture Notes in Artificial Intelligence, AIMSA 2004, 3192:216-225, 2004. [PDF]
• Prediction of implicit protein-protein interaction by optimal associative feature mining, J.-H. Eom, J.-H. Chang and B.-T. Zhang, Lecture Notes in Computer Science, IDEAL 2004, 3177:85-91, 2004. [PDF]
• PromSearch: a hybrid approach to human core-promoter prediction, B.H. Kim, S.B. Park, and B.-T. Zhang, Lecture Notes in Computer Science, IDEAL 2004, 3177:125-131, 2004. [PDF]
• Stock trading by modelling price trend with dynamic Bayesian networks, J. O, J. W. Lee, S.-B. Park and B.-T. Zhang, Lecture Notes in Computer Science, IDEAL 2004, 3177:794-799, 2004. [PDF]
• Prediction of the risk types of human papillomaviruses by support vector machines, J.-G. Joung, S. J. O, and B.-T. Zhang, Lecture Notes in Artificial Intelligence, PRICAI 2004, 3157:723-731, 2004. [PDF]
• Computational methods for identification of human microRNA precursors, J.-W. Nam, W.-J. Lee, and B.-T. Zhang, Lecture Notes in Artificial Intelligence, PRICAI 2004, 3157:732-741, 2004. [PDF]
• Multi-objective evolutionary probe design based on thermodynamic criteria for HPV detection, I.-H. Lee, S. Kim, and B.-T. Zhang, Lecture Notes in Artificial Intelligence, PRICAI 2004, 3157:742-750, 2004. [PDF]
• Two-step genetic programming for optimization of an RNA common-structure, J.W. Nam, J.G. Joung, Y. S. Ahn, and B.-T. Zhang, Lecture Notes in Computer Science, EvoBio 2004, 3005:73-83, 2004. [PDF]
• Korean compound noun decomposition using syllabic information only, S.-B. Park, J.-H. Chang, and B.-T. Zhang, Lecture Notes in Computer Science, CICLing 2004, 2945:143-154, 2004. [PDF]
• BioPubMiner: machine learning component-based biomedical information analysis platform, J. H. Eom and B.-T. Zhang, Lecture Notes in Computer Science, CIT 2004, 3356:11-20, 2004. [PDF]
• Adaptive neural network-based clustering of yeast protein-protein interactions, J. H. Eom and B.-T. Zhang, Lecture Notes in Computer Science, CIT 2004, 3356:49-57, 2004. [PDF]
• A lab-on-a-chip module for bead separation in DNA-based concept learning, Lim, H.-W., Jang, H.-M., Ha, S.-M., Chai, Y.-G., Yoo, S.-I., and Zhang, B.-T., Lecture Notes in Computer Science, DNA 9, 2943:1-10, 2004. [PDF]
• RCA-based detection methods for resolution refutation, Lee, I.-H., Park, J. Y., Chai, Y.-G., and Zhang, B.-T, Lecture Notes in Computer Science, DNA 9, 2943:32-36, 2004. [PDF]
• Ligation module for in-vitro selection in DNA computing, D. van Noort, I. H. Lee, L. F. Landweber, and B. T. Zhang, SPIE International Symposium on Smart Materials, Nano-, and Micro-Smart Systems, pp. 28-34, 2004. [PDF]
• PDMS valves in DNA computers, D. van Noort and B.-T. Zhang, SPIE International Symposium on Smart Materials, Nano-, and Micro-Smart Systems, pp. 214-220, 2004. [PDF]
• Experimental analysis of ε-multiobjective evolutionary algorithm, I.-H. Lee, S.-Y. Shin, and B.-T. Zhang, Proc. of 5th International Conference on Simulated Evolution and Learning (SEAL 2004), SWP-1/127, 2004. [PDF]
• A Bayesian algorithm for in vitro molecular evolution of pattern classifiers, B.-T. Zhang and H.-Y. Jang, Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), pp.294-303, 2004. [PDF]
• Construction of C-reactive protein-binding aptamer as a module of the DNA computing system for diagnosing cardiovascular diseases, S. D. Kim, J. S. Ryu, H.-K. Yi, S.-C. Kim, and B.-T. Zhang, Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), pp.334-343, 2004.
• Efficient initial pool generation for weighted graph problems using parallel overlap assembly, Lee, J. Y., Lim, H.-W., Yoo, S.-I., Zhang, B.-T., and Park, T. H., Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), pp.357-364, 2004.
• DNA-based perceptron and application to binary classification of gene expression, Lim, H.-W., Lee, J. Y., Kim, S. N., Yoo, S.-I., Park, T. H., and Zhang, B.-T., Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), p.439, 2004.
• Mathematical modeling and simulation of denaturation temperature gradient polymerase chain reaction, Lee, J. Y., Lim, H.-W., Yoo, S.-I., Zhang, B.-T., and Park, T. H., Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), p.444, 2004.
• Oligonucleotide-based theorem proving by cross-linking gold nanoparticle assembly, Park, J.-Y., Kim, T.-G., Lee, I.-H., Park, J.-G., Zhang, B.-T., and Chai, Y.-G., Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), p.446, 2004.
• Simulation of DNA hybridization chain reaction based on thermodynamics and artificial chemistry, Shin, S.-Y., Jang, H.-Y., Tak, M.-H., and Zhang, B.-T., Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), p.451, 2004.
• Solving the monkey and banana problem using DNA computing, Park, E.-J., Nam, J.-W., Lee, I.-H., and Zhang, B.-T., Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), p.452, 2004.

• A unified Bayesian framework for evolutionary learning and optimization, Zhang, B.-T., Advances in Evolutionary Computing, Chapter 15, pp. 393-412, Springer-Verlag, 2003. [PDF]
• Bayesian network classifiers for gene expression analysis, Zhang, B.-T. and Hwang, K.-B., A Practical Approach to Microarray Data Analysis, Chapter 8, pp. 150-165, Kluwer Academic Publishers, 2003.
• Self-organizing latent lattice models for temporal gene expression profiling, Zhang, B.-T, Yang, J. and Chi, S. W., Machine Learning, 52(1/2):67-89, 2003. [PDF]
• Word sense disambiguation by learning decision trees from unlabeled data, Park, S.-B., Zhang, B.-T., and Kim, Y. T., Applied Intelligence, 19(1):27-38, 2003. [PDF]
• Genetic mining of HTML structures for effective web-document retrieval, Kim, S. and Zhang, B.-T., Applied Intelligence, 18(3):243-256, 2003. [PDF]
• Identification of novel anti-angiogenic factors by in silico functional gene screening method, Lee, S.-K., Choi, Y. S., Cha, J., Moon, E.-J., Lee, S.-W., Bae, M.-K., Sohn, T.-K., Won, Y., Ma, S., Kong, E. B., Lee, H., Lim, S., Chang, D., Kim, Y.-J., Kim, C. W., Zhang, B.-T., Kim, K.-W, Journal of Biotechnology, 105(1-2):51-60, 2003. [PDF]
• Mining the risk types of human papillomavirus (HPV) by AdaCost, Park, S.-B., S. Hwang, and Zhang, B.-T., Lecture Notes in Computer Science, 2736:403-412, 2003. [PDF]
• Automatic webpage classification enhanced by unlabeled data, Park, S.-B. and Zhang, B.-T., Lecture Notes in Computer Science, 2690:821-825, 2003. [PDF]
• Classification of the risk types of human papillomavirus by decision trees, Park, S.-B., S. Hwang, and Zhang, B.-T., Lecture Notes in Computer Science, 2690:540-544, 2003. [PDF]
• An empirical study on dimensionality optimization in text mining for linguistic knowledge acquisition, Kim, Y.-S., Chang, J.-H., and Zhang, B.-T., Lecture Notes in Artificial Intelligence, 2637:111-116, 2003. [PDF]
• Large scale unstructured document classification using unlabeled data and syntactic information, Park, S.-B. and Zhang, B.-T., Lecture Notes in Artificial Intelligence, 2637:88-99, 2003. [PDF]
• NACST/Seq: a sequence design system with multiobjective optimization, Kim, D., Shin, S.-Y., Lee, I.-H., and Zhang, B.-T., Lecture Notes in Computer Science, 2568:242-251, 2003. [PDF]
• DNA implementation of theorem proving with resolution refutation in propositional logic, Lee, I.-H., Park, J.-Y., Jang, H.-M., Chai, Y.-G., and Zhang, B.-T., Lecture Notes in Computer Science, 2568:156-167, 2003. [PDF]
• Version space learning with DNA molecules, Lim, H.-W., Yun, J.-E., Jang, H.-M., Chai, Y.-G., Yoo, S.-I., and Zhang, B.-T., Lecture Notes in Computer Science, 2568:143-155, 2003. [PDF]
• Temperature gradient-based DNA computing for graph problems with weighted edges, Lee, J. Y., Shin, S.-Y., Augh, S. J., Park, T. H., and Zhang, B.-T., Lecture Notes in Computer Science, 2568:73-84, 2003. [PDF]
• Classification of human Papillomavirus (HPV) risk type via text mining, Park, S.-B., Hwang, S., and Zhang, B.-T., Genomics & Informatics, 1(2):80-86, 2003. [PDF]
• Gene expression pattern analysis via latent variable models coupled with topographic clustering, Chang, J.-H., Chi, S. W., and Zhang, B.-T., Genomics & Informatics, 1(1): 32-39, 2003. [PDF]
• Molecular immunocomputing with application to alphabetical pattern recognition mimics the characterization of ABO blood type, Kim, S. D., Shin, K.-R., and Zhang, B.-T., Proceedings of the 2003 Congress on Evolutionary Computation, 4:2549-2556, 2003. [PDF]
• DNA sequence optimization using constrained multi-objective evolutionary algorithm, Lee, I.-H., Shin, S.-Y., and Zhang, B.-T., Proceedings of the 2003 Congress on Evolutionary Computation (CEC2003), 4:2270-2276, 2003. [PDF]
• Text chunking by combining hand-crafted rules and memory-based learning, Park, S.-B. and Zhang, B.-T., Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL2003), pp. 497-504, 2003. [PDF]
• Molecular evolutionary computing lab-on-a-chip: a first design and simulation, B.-T. Zhang, H.-Y. Jang, D.-Y. Cho, and I.-H. Lee, Proceedings of the 10th International Conference on Neural Information Processing, pp. 516-519, 2003.
• Effectiveness of denaturation temperature gradient-polymerase chain reaction for biased DNA algorithms, Lee, J. Y., Zhang, B.-T., and Park, T. H., Preliminary Proceedings of the Ninth International Meeting on DNA Based Computers (DNA9), p. 208, 2003. [PDF]
• DNA computing complexity analysis using DNA/DNA hybridization kinetics, Shin, S.-Y., Lee, E. J., Park, T. H., and Zhang, B.-T., Preliminary Proceedings of the Ninth International Meeting on DNA Based Computers (DNA9), p. 207, 2003. [PDF]
• RCA-based detection methods for resolution refutation, Lee, I.-H., Park, J. Y., Chai, Y.-G., and Zhang, B.-T., Preliminary Proceedings of the Ninth International Meeting on DNA Based Computers (DNA9), pp. 42-46, 2003. [PDF]
• A lab-on-a-chip module for bead separation in DNA-based concept learning, Lim, H.-W., Jang, H.-M., Ha, S.-M., Chai, Y.-G., Yoo, S.-I., and Zhang, B.-T., Preliminary Proceedings of the Ninth International Meeting on DNA Based Computers (DNA9), pp. 9-18, 2003. [PDF]
• Mining the risk types of human papillomavirus (HPV) by cost-sensitive Learning, Hwang, S., Park, S.-B., and Zhang, B.-T., Proceedings of PAKDD2003 Workshop on Biological Data Mining, pp. 107-118, 2003.

• Analysis of gene expression profiles and drug activity patterns by clustering and Bayesian network learning, Chang, J.-H., Hwang, K.-B., and Zhang, B.-T., Methods of Microarray Data Analysis II, Chapter 11, pp. 169-184, Kluwer Academic Publishers, 2002. [PDF]
• Applying machine learning techniques to analysis of gene expression data: cancer diagnosis, Hwang, K.-B., Cho, D.-Y., Park, S.-W., Kim, S.-D., and Zhang, B.-T., Methods of Microarray Data Analysis, Chapter 12, pp. 167-182, Kluwer Academic Publishers, 2002. [PDF]
• A Bayesian evolutionary approach to the design and learning of heterogeneous neural trees, Zhang, B.-T., Integrated Computer-Aided Engineering, 9(1):73-86, 2002. [PDF]
• Target word selection using WordNet and data-driven models in machine translation, Kim, Y., Chang, J.-H., and Zhang, B.-T., Lecture Notes in Artificial Intelligence, 2417:607, 2002. [PDF]
• Topic extraction from text documents using multiple-cause networks, Chang, J.-H., Lee, J. W., Kim, Y., and Zhang, B.-T., Lecture Notes in Artificial Intelligence, 2417:434-443, 2002. [PDF]
• Construction of large-scale Bayesian networks by local to global search, Hwang, K.-B., Lee, J. W., Chung, S.-W., and Zhang, B.-T., Lecture Notes in Artificial Intelligence, 2417:375-384, 2002. [PDF]
• Behavior evolution of autonomous mobile robot (AMR) using genetic programming based on evolvable hardware, Sim, K.-B., Lee, D.-W., and Zhang, B.-T., International Journal of Fuzzy Logic and Intelligent Systems, 2(1):20-25, 2002. [PDF]
• A Comparative evaluation of data-driven models in translation selection of machine translation, Kim, Y.-S., Chang, J.-H., and Zhang, B.-T., Proceedings of the 19th International Conference on Computational Linguistics (COLING2002), 1:453-459, 2002. [PDF]
• A boosted maximum entropy model for learning text chunking, Park, S.-B. and Zhang, B.-T., Proceedings of the Nineteenth International Conference on Machine Learning (ICML2002), pp. 482-489, 2002. [PDF]
• Stock trading system using reinforcement learning with cooperative agents, O, Jangmin, Lee, J.-W., and Zhang, B.-T., Proceedings of the Nineteenth International Conference on Machine Learning (ICML2002), pp. 451-458, 2002. [PDF]
• Version space learning with DNA molecules, Lim, H.-W., Yun, J.-E., Jang, H.-M., Chai, Y.-G., Yoo, S.-I., and Zhang, B.-T., Preliminary Proceedings of the Eighth International Meeting on DNA Based Computers (DNA8), pp. 261-270, 2002. [PDF]
• DNA implementation of theorem proving with resolution refutation in propositional logic, Lee, I.-H., Park, J.-Y., Jang, H.-M., Chai, Y.-G., and Zhang, B.-T., Preliminary Proceedings of the Eighth International Meeting on DNA Based Computers (DNA8), pp. 251-260, 2002. [PDF]
• NACST/Seq: A sequence design system with multiobjective optimization, Kim, D.-M., Shin, S.-Y., Lee, I.-H., and Zhang, B.-T., Preliminary Proceedings of the Eighth International Meeting on DNA Based Computers (DNA8), pp. 241-250, 2002. [PDF]
• Temperature gradient-based DNA computing for graph problems with weighted edges, Lee, J.-Y., Shin, S.-Y., Augh, S.-J., Park, T.-H., and Zhang, B.-T., Preliminary Proceedings of the Eighth International Meeting on DNA Based Computers (DNA8), pp. 41-50, 2002. [PDF]
• Evolutionary optimization by distribution estimation with mixtures of factor analyzers, Cho, D.-Y. and Zhang, B.-T., Proceedings of the 2002 Congress on Evolutionary Computation (CEC2002), 2:1396-1401, 2002. [PDF]
• Evolutionary sequence generation for reliable DNA computing, Shin, S.-Y., Kim, D.-M., Lee, I.-H., and Zhang, B.-T., Proceedings of the 2002 Congress on Evolutionary Computation (CEC2002), 1:79-84, 2002. [PDF]

• Personalized web-document filtering using reinforcement learning, Zhang, B.-T. and Seo, Y.-W., Applied Artificial Intelligence, 15(7):665-685, 2001. [PDF]
• System identification using evolutionary Markov chain monte carlo, Zhang, B.-T. and Cho, D.-Y., Journal of Systems Architecture, 47(7):587-599, 2001. [PDF]
• Learning-based intrasentence segmentation for efficient translation of long sentences, Kim, S.-D., Zhang, B.-T., and Kim, Y. T., Machine Translation, 16(3):151-174, 2001. [PDF]
• Collocation dictionary optimization using WordNet and k-nearest neighbor learning, Kim, Y.-S., Zhang, B.-T., and Kim, Y.-T., Machine Translation, 16(2):89-108, 2001. [PDF]
• Document indexing using independent topic extraction, Kim, Y.-H. and Zhang, B.-T., Proceedings of the Third International Conference on Independent Component Analysis and Signal Separation, pp. 557-562, 2001. [PDF]
• Concurrent evolution of neural networks and their data Sets, Joung, J.-G. and Zhang, B.-T., Proceedings of the 8th International Conference on Neural Information Processing (ICONIP-2001), 1:115-120, 2001. [PDF]
• Customer data mining and visualization by generative topographic mapping methods, Yang, J. and Zhang, B.-T., Proceedings of the International Workshop on Visual Data Mining, pp. 55-66, 2001. [PDF]
• Adaptive humor recommendation, Lee, J.-W. and Zhang, B.-T., Proceedings of the 2nd International Symposium on Advanced Intelligent Systems, 2:321-325, 2001.
• Document filtering boosted by unlabeled data, Park, S.-B. and Zhang, B.-T., Proceedings of the 2001 IEEE International Symposium on Industrial Electronics (ISIE2001), 1:328-333, 2001. [PDF]
• Evolutionary learning of web-document structure for information retrieval, Kim, S. and Zhang, B.-T., Proceedings of the 2001 Congress on Evolutionary Computation (CEC2001), 2:1253-1260, 2001. [PDF]
• Evolutionary calibration of sensors using genetic programming on evolvable hardware, Seok, H.-S. and Zhang, B.-T., Proceedings of the 2001 Congress on Evolutionary Computation (CEC2001), 1:630-634, 2001. [PDF]
• Continuous estimation of distribution algorithms with probabilistic principal component analysis, Cho, D.-Y. and Zhang, B.-T., Proceedings of the 2001 Congress on Evolutionary Computation (CEC2001), 1:521-526, 2001. [PDF]
• Bayesian evolutionary algorithms for continuous function optimization, Shin, S.-Y. and Zhang, B.-T., Proceedings of the 2001 Congress on Evolutionary Computation (CEC2001), 1:508-515, 2001. [PDF]
• Actively searching for committees of RBF networks using Bayesian evolutionary computation, Joung, J.-G. and Zhang, B.-T., Proceedings of the 2001 Congress on Evolutionary Computation (CEC2001), 1:372-377, 2001. [PDF]
• Convergence properties of Bayesian evolutionary algorithms with population size greater than 1, Lee, S.-E., Zhang, B.-T., and Doucet, A., Proceedings of the 2001 Congress on Evolutionary Computation (CEC2001), 1:326-331, 2001. [PDF]
• Using stochastic Helmholtz machine for text learning, Chang, J.-H. and Zhang, B.-T., Proceedings of the 19th International Conference on Computer Processing of Oriental Languages (ICCPOL2001), pp. 453-458, 2001. [PDF]
• Distributed clustering of Korean verbs using self-organizing maps, Park, S.-B. and Zhang, B.-T., Proceedings of the 19th International Conference on Computer Processing of Oriental Languages (ICCPOL2001), pp. 309-312, 2001. [PDF]
• Combining rule-based method and k-NN for chunking Korean text, Park, S.-B. and Zhang, B.-T., Proceedings of the 19th International Conference on Computer Processing of Oriental Languages (ICCPOL2001), pp. 225-230, 2001. [PDF]
• Function optimization with latent variable models, Shin, S.-Y., Cho, D.-Y., and Zhang, B.-T., Proceedings of the Third International Symposium on Adaptive Systems (ISAS2001), pp. 145-152, 2001. [PDF]

• Bayesian evolutionary optimization using Helmholtz machines, Zhang, B.-T. and Shin, S.-Y., Lecture Notes in Computer Science, 1917:827-836, 2000. [PDF]
• Building optimal committees of genetic programs, Zhang, B.-T. and Joung, J.-G., Lecture Notes in Computer Science, 1917:231-240, 2000. [PDF]
• Bayesian methods for efficient genetic programming, Zhang, B.-T., Genetic Programming and Evolvable Machines, 1(3):217-242, 2000. [PDF]
• Evolving complex group behaviors using genetic programming with fitness switching, Zhang, B.-T. and Cho, D.-Y., Artificial Life and Robotics, 4(2):103-108, 2000. [PDF]
• Comparison of selection methods for evolutionary optimization, Zhang, B.-T. and Kim, J.-J., Evolutionary Optimization, 2(1):55-70, 2000. [PDF]
• Learning constructive RBF networks by active data selection, Park, S.-W. and Zhang, B.-T., Proceedings of the International Conference on Neural Information Processing (ICONIP-2000), 2:1411-1415, 2000. [PDF]
• Boosting linear perceptrons for unbalanced data, O, Jangmin and Zhang, B.-T., Proceedings of the International Conference on Neural Information Processing (ICONIP-2000), 1:642-645, 2000. [PDF]
• SCAI experiments on TREC-9, Kim, Y.-H., Kim, S., Eom, J.-H., and Zhang, B.-T., Proceedings of the Ninth Text REtrieval Conference (TREC-9), pp. 392-399, 2000. [PDF]
• Learning robot behaviors by evolving genetic programs, Lee, K.-J. and Zhang, B.-T., Proceedings of the 26th International Conference on Industrial Electronics, Control and Instrumentation (IECON-2000), 4:2867-2872, 2000. [PDF]
• Behavior evolution of autonomous mobile robot using genetic programming based on evolvable hardware, Lee, D.-W., Ban, C.-B., Sim, K.-B., Seok, H.-S., Lee, K.-J., and Zhang, B.-T., Proceedings of the 2000 IEEE International Conference on Systems, Man, and Cybernetics (SMC2000), 5:3835-3840, 2000. [PDF]
• Reducing parsing complexity by intra-sentence segmentation based on maximum entropy model, Kim, S.-D., Zhang, B.-T., and Kim, Y.-T., Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-2000), pp. 164-171, 2000. [PDF]
• Word sense disambiguation by learning from unlabeled data, Park, S.-B., Zhang, B.-T., and Kim, Y.-T., Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics (ACL'2000), pp. 547-554, 2000. [PDF]
• Web-document retrieval by genetic learning of importance factors for HTML tags, Kim, S. and Zhang, B.-T., Proceedings of the Sixth Pacific Rim International Conference on AI (PRICAI'2000) Workshop on Text and Web Mining, pp. 13-23, 2000. [PDF]
• Extracting topic words and clustering documents using probabilistic graphical models, Shin, H.-J. and Zhang, B.-T., Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2000) Workshop on Text Mining, pp. 107-108, 2000. [PDF]
• Text filtering by boosting naive Bayes classifiers, Kim, Y.-H., Hahn, S.-Y., and Zhang, B.-T., Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2000), pp. 168-175, 2000. [PDF]
• Bayesian evolutionary algorithms for evolving neural tree models of time series data, Cho, D.-Y. and Zhang, B.-T., Proceedings of the 2000 Congress on Evolutionary Computation (CEC00), 2:1451-1458, 2000. [PDF]
• Convergence properties of incremental Bayesian evolutionary algorithms with single Markov chains, Zhang, B.-T., Paaß, G., and Mühlenbein, H., Proceedings of the 2000 Congress on Evolutionary Computation (CEC00), 2:938-945, 2000. [PDF]
• Genetic programming of process decomposition strategies for evolvable hardware, Seok, H.-S., Lee, K.-J., Zhang, B.-T., Lee, D.-W., and Sim, K.-B., Proceedings of the Second NASA/DoD Workshop on Evolvable Hardware (EH-2000), pp. 25-34, 2000. [PDF]
• Bayesian evolutionary algorithms for learning and optimization, Zhang, B.-T., Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000) Workshop Program, pp. 220-222, 2000. [PDF]
• Learning user's preferences by analyzing web-browsing behaviors, Seo, Y.-W. and Zhang, B.-T., Proceedings of the Fourth International Conference on Autonomous Agents (Agents-2000), pp. 381-387, 2000. [PDF]
• Evolving neural trees for time series prediction using Bayesian evolutionary algorithms, Zhang, B.-T. and Cho, D.-Y., Proceedings of the First IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (ECNN2000), pp. 17-23, 2000. [PDF]
• An on-line learning method for object-locating robots using genetic programming on evolvable hardware, Seok, H.-S., Lee, K.-J., Joung, J.-G., and Zhang, B.-T., Proceedings of the Fifth International Symposium on Artificial Life and Robotics (AROB'00), 1:321-324, 2000. [PDF]
• A Reinforcement learning agent for personalized information filtering, Seo, Y.-W. and Zhang, B.-T., Proceedings of International Conference on Intelligent User Interfaces (IUI'2000), pp. 248-251, 2000. [PDF]

• Co-evolutionary fitness switching: learning complex collective behaviors using genetic programming, Zhang, B.-T. and Cho, D.-Y., Advances in Genetic Programming, vol. 3, Chapter 18, pp. 425-445, MIT Press, 1999. [PS]
• Genetic programming with active data selection, Zhang, B.-T. and Cho, D.-Y., Lecture Notes in Artificial Intelligence, 1585:146-153, 1999. [PDF]
• SCAI TREC-8 experiments, Shin, D.-H, Kim, Y.-H., Kim, S., Eom, J.-H., Shin, H.-J., and Zhang, B.-T., Proceedings of the Eighth Text REtrieval Conference (TREC-8), pp. 511-518, 1999. [PS]
• Compound noun decomposition using a Markov model, Lee, J.-W., Zhang, B.-T., and Kim, Y.-T., Proceedings of the Machine Translation Summit VII, pp. 427-431, 1999. [PS]
• Bayesian genetic programming, Zhang, B.-T., Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'99) Workshop Program, pp. 68-70, 1999. [PS]
• Genetic programming with incremental data inheritance, Zhang, B.-T. and Joung, J.-G., Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'99), 2:1217-1224, Morgan Kaufmann, 1999. [PS]
• Combining locally trained neural networks by introducing a reject class, Kim, S.-J. and Zhang, B.-T., Proceedings of the International Joint Conference on Neural Networks (IJCNN'99), 6:4043-4047, 1999. [PDF]
• Temporal pattern recognition using a spiking neural network with delays, Sohn, J.-W., Zhang, B.-T., and Kaang, B.-K., Proceedings of the International Joint Conference on Neural Networks (IJCNN'99), 4:2590-2593, 1999. [PDF]
• Solving travelling salesman problems using molecular programming, Shin, S.-Y., Zhang, B.-T., and Jun, S.-S., Proceedings of the 1999 Congress on Evolutionary Computation (CEC99), 2:994-1000, 1999. [PDF]
• A Bayesian framework for evolutionary computation, Zhang, B.-T., Proceedings of the 1999 Congress on Evolutionary Computation (CEC99), 1:722-728, 1999. [PDF]
• Time series prediction using committee machines of evolutionary neural trees, Zhang, B.-T. and Joung, J.-G., Proceedings of the 1999 Congress on Evolutionary Computation (CEC99), 1: 281-286, 1999. [PDF]
• Effects of selection schemes in genetic programming for time series analysis, Kim, J.-J. and Zhang, B.-T., Proceedings of the 1999 Congress on Evolutionary Computation (CEC99), 1: 252-258, 1999. [PDF]
• Forecasting high-frequency financial time series with evolutionary neural trees: the case of Hang-Seng stock index, Chen, S.-H., Wang, H.-S., and Zhang, B.-T., Proceedings of the 1999 International Conference on Artificial Intelligence (IC-AI'99), pp. 437-443, 1999. [PS]
• Genetic programming-based alife techniques for evolving collective robotic intelligence, Cho, D.-Y and Zhang, B.-T., Proceedings of the Fourth International Symposium on Artificial Life and Robotics (AROB'99), pp. 236-239, 1999. [PDF]

• Code optimization for DNA computing of maximal cliques, Zhang, B.-T. and Shin, S.-Y., Advances in Soft Computing: Engineering Design and Manufacturing, Springer-Verlag, 1998. [PDF]
• Comparison of selection schemes for machine layout design, Kim, J.-J. and Zhang, B.-T., Proceedings of the Second Asia Pacific Conference on Simulated Evolution and Learning (SEAL'98), vol. 2, 1998. [PDF]
• Genetic programming with active data selection, Zhang, B.-T. and Cho, D.-Y., Proceedings of the Second Asia Pacific Conference on Simulated Evolution and Learning (SEAL'98), Lecture Notes in Computer Science, 1585:146-153, 1998. [PDF]
• A Two-stage retrieval model for the TREC-7 ad hoc task, Shin, D.-H. and Zhang, B.-T., Proceedings of the Seventh Text REtrieval Conference (TREC-7), pp. 501-507, 1998. [PDF]
• Active data partitioning for building mixture models, Kim, S.-J. and Zhang, B.-T., Proceedings of the International Conference on Neural Information Processing (ICONIP'98), 2:854-857, 1998. [PDF]
• Molecular algorithms for efficient and reliable DNA computing, Zhang, B.-T. and Shin, S.-Y., Proceedings of the Third Annual Genetic Programming Conference (GP-98), pp. 735-742, Morgan Kaufmann, 1998. [PDF]
• Fitness switching: evolving complex group behaviors using genetic programming, Zhang, B.-T. and Cho, D.-Y., Proceedings of the Third Annual Genetic Programming Conference (GP-98), 4(2):431-439, Morgan Kaufmann, 1998. [PDF]
• Genetic programming of multi-agent cooperation strategies for table transport, Cho, D.-Y. and Zhang, B.-T., Proceedings of the Third Asian Fuzzy Systems Symposium (AFSS'98), pp.170-175, 1998. [PDF]
• Evolution of herding behavior of multiple autonomous mobile robots, Zhang, B.-T. and Hong, Y.-J., Proceedings of the Third International Symposium on Artificial Life and Robotics (AROB'98), vol. 1, pp. 166-169, 1998. [PDF]

• Evolutionary induction of sparse neural trees, Zhang, B.-T., Ohm, P., and Mühlenbein, H., Evolutionary Computation, 5(2):213-236, 1997. [PDF]
• Evolutionary neural trees for modeling and predicting complex systems, Zhang, B.-T., Ohm, P., and Mühlenbein, H., Engineering Applications of Artificial Intelligence, 10(5):473-483, 1997. [PDF]
• Enhancing robustness of genetic programming at the species level, Zhang, B.-T. and Joung, J.-G., Proceedings of the Second Annual Genetic Programming Conference (GP-97), pp. 336-342, Morgan Kaufmann, 1997. [PDF]
• Using a genetic algorithm for communication link partitioning, Lee, J.-H., Choi, Y.-H., Zhang, B.-T., and Kim, C.-S., Proceedings of 1997 IEEE International Conference on Evolutionary Computation (CEC'97), pp. 581-584, 1997. [PDF]
• Active learning agents with artificial neural brains, Zhang, B.-T., Proceedings of the International Conference on Cognitive Science (ICCS'97), pp. 118-123, 1997. [PDF]
• A multinet neural architecture for evolving collective robotic intelligence, Zhang, B.-T. and Hong, Y.-J., Proceedings of the 1997 International Conference on Neural Information Processing (ICONIP'97), 2:971-974, 1997. [PDF]
• An evolutionary method for active learning of mobile robot path planning, Zhang, B.-T. and Kim, S.-H., Proceedings of 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA'97), pp. 312-317, 1997. [PDF]
• Evolutionary design of neural trees for heart rate prediction, Zhang, B.-T. and Joung, J.-G., Soft Computing in Engineering Design and Manufacturing, pp. 93-102, Springer, 1997. [PDF]
• A Taxonomy of control schemes for genetic code growth, Zhang, B.-T., Proceedings of the Seventh International Conference on Genetic Algorithms (ICGA-97) Workshop on Evolutionary Computation with Variable Size Representation, 1997. [PDF]
• Evolving cooperation strategies for multiple mobile robots, Hong, Y.-J. and Zhang, B.-T., Proceedins of the Second Asian Control Conference (ASCC'97), 2:627-630, 1997. [PDF]

• Adaptive fitness functions for dynamic growing/pruning of program trees, Zhang, B.-T. and Mühlenbein., H., Advances in Genetic Programming, vol. 2, Chapter 12, pp. 241-256, MIT Press, 1996.
• Building software agents for information filtering on the internet: a genetic programming approach, Zhang, B.-T., Kwak, J.-H., and Lee, C.-H., Late Breaking Papers at the Genetic Programming 1996 Conference (GP-96), p. 196, 1996. [PDF]

• Balancing accuracy and parsimony in genetic programming, Zhang, B.-T. and Mühlenbein, H., Evolutionary Computation, vol. 3, no. 1, pp. 17-38, 1995. [PDF]
• Artificial neural nets, adaptive genetic programming, and intelligent learning machines, Zhang, B.-T., VeKNI Nachrichten, 41:17-31, 1995.
• Water pollution prediction with evolutionary neural trees, Zhang, B.-T., Ohm, P., and Mühlenbein, H., Proceedings of the 14th Internationl Joint Conference on Artificial Intelligence (IJCAI-95) Workshop on AI and the Environment, 1995. [PDF]
• Bayesian inference, minimum description length principle and learning by genetic programming, Zhang, B.-T. and Mühlenbein, H., Proceedings of the 12th International Conference on Machine Learning (ICML'95) Workshop on Genetic Programming, pp. 1-5, 1995. [PDF]
• MDL-based fitness functions for learning parsimonious programs, Zhang, B.-T. and Mühlenbein, H., Proceedings of the 1995 AAAI Fall Symposium on Genetic Programming, pp. 122-126, AAAI Press, 1995. [PDF]
• Learning to predict by evolutionary neural trees, Zhang, B.-T., Ohm, P., and Mühlenbein, H., Proceedings of the World Congress on Neural Networks (WCNN'95), 1:823-826, 1995. [PDF]

• Accelerated learning by active example selection, Zhang, B.-T., International Journal of Neural Systems, 5(1):67-75, 1994. [PDF]
• Effects of Occam's razor in evolving sigma-pi neural nets, Zhang, B.-T., Lecture Notes in Computer Science, 866:462-471, 1994. [PDF]
• Active learning algorithms for neural networks, Zhang, B.-T., Proceedings of the First International Conference on Neural Information Processing (ICONIP'94), 3:1720-1725, 1994. [PDF]
• Using genetic algorithms for automatic construction of higher-order neural models, Zhang, B.-T. and Mühlenbein, H., Proceedings of the First International Conference on Neural Information Processing (ICONIP'94), vol. 1, pp. 168-173, 1994. [PDF]
• Synthesis of sigma-pi neural networks by the breeder genetic programming, Zhang, B.-T. and Mühlenbein, H., Proceedings of the First IEEE Conference on Evolutionary Computation (ICEC'94), 1:318-323, 1994. [PDF]
• An incremental learning algorithm that optimizes network size and sample size in one trial, Zhang, B.-T., Proceedings of IEEE International Conference on Neural Networks (ICNN'94), 1:215-220, 1994. [PDF]
• Statistical inference as a theoretical foundation of genetic algorithms, Mühlenbein, H. and Zhang, B.-T., Proceedings of the Joint Meeting of Real World Computing Partnership (RWCP), 1994. [PDF]
• Selecting a critical subset of given examples during learning, Zhang, B.-T., Proceedings of the International Conference on Artificial Neural Networks (ICANN'94), pp. 517-520, Springer-Verlag, 1994. [PDF]
• Genetic breeding of novel neural architectures, Zhang, B.-T. and Mühlenbein, H., Proceedings of the Second European Congress on Intelligent Techniques and Soft Computing, pp. 1265-1269, 1994. [PDF]

• Evolving optimal neural networks using genetic algorithms with Occam's razor, Zhang, B.-T. and Mühlenbein, H., Complex Systems, 7(3):199-220, 1993. [PDF]
• A genetic neural learning engine for artificial intelligence, Zhang, B.-T., VeKNI Nachrichten, Stuttgart, pp. 239-249, 1993.
• Learning by Genetic Neural Evolution (in German), Zhang, B.-T., PhD Dissertation, University of Bonn, Germany, published as DISKI Series, vol. 16, ISBN 3-929037-16-6, 268 pages, Infix-Verlag, St. Augustin/Bonn, July 1992.
• Genetic programming of minimal neural nets using Occam's razor, Zhang, B.-T. and Mühlenbein, H., Proceedings of the Fifth International Conference on Genetic Algorithms (ICGA-93), pp. 342-349, Morgan Kaufmann, 1993. [PDF]
• Teaching neural networks by genetic exploration, B.T. Zhang, Arbeitspapiere der GMD, No 805, German National Research Center for Computer Science (GMD), St. Augustin/Bonn, November 1993. [PDF]
• Self-development learning: constructing optimal size neural networks via incremental data selection, Zhang, B.-T., Arbeitspapiere der GMD, No 768, German National Research Center for Computer Science (GMD), St. Augustin/Bonn, July 1993. [PDF]
• Learning by incremental selection of critical examples, Zhang, B.-T., Arbeitspapiere der GMD, No 735, German National Research Center for Computer Science (GMD), St. Augustin/Bonn, March 1993. [PDF]
• Neural networks that teach themselves through genetic discovery of novel examples, Zhang B.-T. and Veenker, G., Proceedings of the 1991 IEEE International Joint Conference on Neural Networks (IJCNN'91), 1:690-695, 1991. [PDF]
• Focused incremental learning for improved generalization with reduced training sets, Zhang B.-T. and Veenker, G., Proceedings of the International Conference on Artificial Neural Networks (ICANN'91), pp. 227-232, 1991. [PDF]
• Distributed parallel cooperative problem-solving with a voting and election system of neural networks, Zhang, B.-T., Parallel Processing in Neural Systems and Computers, pp. 513-516, 1990. [PDF]
• Morphological analysis and synthesis by automated discovery and acquisition of linguistic rules, Zhang, B.-T. and Kim, Y.-T., Proceedings of the 13th International Conference on Computational Linguistics (COLING-90), pp. 431-436, 1990. [PDF]
• An English-Korean system for human assisted language translation, Kang, S.-S., Shim, K.-S., Zhang, B.-T., Kwon, H.-C., Woo, C.-S., and Kim, Y.-T., Proceedings of the 1987 IEEE Region 10 Conference (TENCON'87), pp. 509-515, 1987. [PDF]