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]
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]
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]
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]
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]
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]
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]
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]
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]
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.
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]
Bayesian evolutionary hypergraph learning for predicting cancer clinical outcomes, S.-J Kim, J.-W. Ha, and B.-T. Zhang, Journal of Biomedical Informatics, 2014 (in press).
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]
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]
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]
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]
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. [PS]
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 methods for efficient genetic programming, Zhang,
B.-T., Genetic Programming and Evolvable Machines, 1(3):217-242, 2000. [PDF]
Bayesian evolutionary optimization using Helmholtz machines,
Zhang, B.-T. and Shin, S.-Y., Lecture Notes in Computer Science,
1917:827-836, 2000. [PS]
Building optimal committees of genetic programs, Zhang, B.-T.
and Joung, J.-G., Lecture Notes in Computer Science, 1917:231-240, 2000. [PS]
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),
vol. 2, pp. 938-945, 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. [PS]
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]
Bayesian genetic programming, Zhang, B.-T., Proceedings of
the Genetic and Evolutionary Computation Conference (GECCO'99) Workshop
Program, pp. 68-70, 1999. [PS]
A Bayesian framework for evolutionary computation, Zhang,
B.-T., Proceedings of the 1999 Congress on Evolutionary Computation
(CEC99), 1:722-728, 1999. [PDF]
Incremental Data Inheritance
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]
Genetic programming with active data selection, Zhang, B.-T.
and Cho, D.-Y., Lecture Notes in Artificial Intelligence, 1585:146-153, 1999. [PDF]
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]
Efficient model induction by a Bayesian evolutionary algorithm with incremental data inheritance, Zhang, B.-T. and Joung, J.-G.,
IEEE Transactions on Evolutionary Computation, 1998. (submitted)
Genetic programming with active data selection, Zhang, B.-T.
and Cho, D.-Y., Lecture Notes in Artificial Intelligence, 1585:146-153, 1999. [PDF]
Adaptive Occam Method/Genetic Programming
Evolutionary induction of sparse neural trees, Zhang, B.-T.,
Ohm, P., and Mühlenbein, H., Evolutionary Computation,
5(2):213-236, 1997. [PS]
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.
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.
Balancing accuracy and parsimony in genetic programming,
Zhang, B.-T. and Mühlenbein, H., Evolutionary Computation, vol.
3, no. 1, pp. 17-38, 1995.
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.
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.
Effects of Occam's razor in evolving sigma-pi neural nets,
Zhang, B.-T., Lecture Notes in Computer Science, 866:462-471, 1994.
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]
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]
Evolvable Hardware
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]
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]
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]
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]
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. [PS]
Selection
Comparison of selection methods for evolutionary optimization, Zhang, B.-T. and Kim, J.-J., Evolutionary
Optimization, 2(1):55-70, 2000. [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]
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.
Coevolution
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.
Optimization
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 (ICEC'97), pp. 581-584, 1997. [PDF]
Evolving Neural Trees
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]
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.
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.
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]
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.
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Last update: February 7, 2014.