- Machine Learning
- Bioinformatics
- Bioinformatics Seminar
Textbook: Computational Methods in Molecular Biology, Steven L. Salzberg(Editor), et al, 1999.
- Biocomputing
- Probabilistic Learning
- Evolutionary Computation
- Adaptive Cooperative Systems
Textbook: Adaptive Cooperative Systems, Martin Beckerman, John Wiley & Son, 1997.
- EC Group Seminar
- Genetic Programming - An Introduction
Textbook: Genentic Programming - An Introduction On the Automatic Evolution of Computer Programs and Its Applications, Wolfgang Banzhaf, Peter Nordin, Robert E. Keller and Frank D. Francone, 1998.
- Evolutionary Algorithms in Theory and Practice
Textbook: Evolutionary Algorithms in Theory and Practice : Evolution Strategies, Evolutionary Programming, Genetic Algorithms, Thomas Back, 1996.
- An Introduction to Genetic Algorithms
Textbook: An Introduction to Genetic Algorithms, Melanie Mitchell, 1996.
- Graduate Courses
- Action-Perception-Learning Cycles (Fall 2012)
Textbook:
[1] Bayesian Time Series Models, Barber, Cemgil, and Chiappa, 2011.
[2] Kalman Filtering and Neural Networks, Haykin, 2001.
[3] Beyond the Kalman Filter, Ristic, Arulampalam, and Gordon, 2004.
- Brain and Computation (Fall 2012)
Textbook:
[1] Fundamentals of Computational Neuroscience, Thomas Trappenberg, Second Edition, 2010.
[2] Principles of Neural Science, Eric R. Kandel, J.H. Schwartz, Thomas M. Jessell, 2000.
- Multisensory Predictive Learning (Fall 2011)
Textbook:
[1] Sensory Cue Integration (Eds.), Trommershaeuser, J., Koerding, K., and Landy, M. S., Oxford University Press, 2011.
[2] Predictions in the Brain: Using Our Past to Generate a Future, (Ed.), Bar, M., Oxford University Press, 2011.
[3] Dynamic Coordination in the Brain: From Neurons to Mind, (Eds.), Von der Malsburg, C., Phillips, W.A., and Singer, W., MIT Press, 2010.
- Brain and Computation (Spring 2010)
Textbook:
[1] Fundamentals of Computational Neuroscience, Thomas Trappenberg, Second Edition, 2010.
[2] Principles of Neural Science, Eric R. Kandel, J.H. Schwartz, Thomas M. Jessell, 2000.
- Probabilistic Graphical Models (Artificial Neural Networks, Studies in Artificial Intelligence and Cognitive Process) (Fall 2009)
Textbook:
[1] Adaptive Cooperative Systems, Beckerman, M., Wiley, 1997.
[2] Pattern Recognition and Machine Learning, Bishop, C. M., Springer, 2006.
[3] Neural Networks: A Comprehensive Foundation, Haykin, S., Prentice Hall, 1999.
[4] Information Theory, Inference, and Learning Algorithms, Mackay, D. J. C., Cambridge Univ.
[5] Hypernetworks: A Molecular Evolutionary Architecture for Cognitive Learning and Memory, Zhang, B.-T., IEEE Computational Intelligence Magazine, 3(3):49-63, 2008
Related Courses: Studies in Artificial Intelligence and Cognitive Process (Fall 2009)
- Computational Models of Intelligence (Spring 2009)
Textbook:
[1] Memory: From Mind to Molecules, L. R. Squire and E. R. Kandel, 2009.
[2] Cortex and Mind: Unifying Cognition, J. M. Fuster, Oxford University Press, 2003.
Related Courses: Computational Neuroscience (Spring 2009)
- Bioinformactics and Practice 1 (JAVA) (Spring 2009)
Textbook: Java: Introduction to Problem Solving and Programming 5th edition, Walter Savitch and Frank M. Carrano , Prentice Hall, 2008.
Related Courses:
Spring 2008,
Spring 2007,
Spring 2006,
Spring 2005,
Spring 2004
- Biological Sequence Anlaysis (Fall 2002)
Textbook: Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Richard Durbin. S. Eddy, A. Krogh, G. Mitchison.
- Bioinformatics and Practice I (Spring 2002)
Textbook: Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Second Edition, Andreas D. Baxevanis and B. F. Francis Ouellette, Wiley Inter-Science, 2001.
- Molecular Intelligence(Knowledge Representation and Reasoning) (Spring 2002)
- Bioinformatics(Machine Learning) (Spring 2001)
Textbook: Bioinformatics: The Machine Learning Approach, P. Baldi and S. Brunak, A Bradford Book, The MIT Press, 1998.
- Intelligent Learning Agents (Spring 2000)
(Advanced Artificial Intelligence)
- Statistical Learning Theory (Spring 1999)
Textbook: Learning from Data: Concepts, Theory, and Methods, V. Cherkassky and F. Mulier, Wiley, 1998.
- Machine Learning (Spring 1998)
Textbook: Machine Learning, T. Mitchell, McGraw-Hill, 1997.
- Undergraduate Courses
- Artificial Intelligence: Cognitive Robotics (Fall 2012)
Textbook:
The Quest for Artificial Intelligence, Nilsson, N. J., Cambridge University Press, 2009.
References:
[1] Cognitive computing I: Multisensory perceptual intelligence in real-world (in Korean), B.-T. Zhang, Mu-Song Yeu, Communications of KIISE, 30(1):75-87, 2012.
[2] Cognitive computing II: Machine vision-language learning in real-life (in Korean), B.-T. Zhang, Dong-Hoon Lee, Communications of KIISE, 30(1):88-100, 2012.
[3] Cognitive computing III: Deep dynamic prediction in real-time (in Korean), B.-T. Zhang, Hyun-Soo Kim, Communications of KIISE, 30(1):101-111, 2012.
[4] Next-generation machine learning technologies (in Korean), B.-T. Zhang, Communications of KIISE, 25(3):96-107, 2007.
-Related Courses:
Spring 2012
- Video Search & Mining (Spring 2012)
Textbook:
[1] Video Search and Mining, D. Schonfeld, C. Shan, D. Tao, and L. Wang (Eds.), 2010.
[2] Video Mining (The International Series in Video Computing), Azriel Rosenfeld, David Doermann and Daniel DeMenthon (Eds.), 2003.
- Brain, Computation, and Neural Learning (Fall 2011)
Textbook:
[1] Fundamentals of Computational Neuroscience, Trappenberg, T., 2nd Ed., 2010.
[2] Cognitive Neuroscience: The Biology of the Mind, M.S. Gazzaniga, R.B. Ivry, and G.R.Mangun, Norton & Company, 3rd Ed., 2008.
[3] Artificial Intelligence: A New Synthesis, Nilsson, N.J., Morgan Kaufmann, 1998.
-Related Courses: Artificial Intelligence, Brain and Computation
- Artificial Intelligence: Biointelligence (Spring 2010)
Textbook:
[1]Artificial Intelligence: A New Synthesis ,Nils J. Nilsson, Morgan Kaufmann, 1998.
[2]Cognitive Neuroscience: The Biology of the Mind, Third Edition ,M.S. Gazzaniga, R.B. Ivry, and G.R. Mangun, Norton & Company, 2008.
-Related Courses:
Fall 2009,
Spring 2009,
Fall 2008,
Spring 2008,
Spring 2007,
Fall 2006,
Spring 2006,
Fall 2005,
Spring 2005,
Fall 2004
- Biotechnology and Computing (Fall 2004)
Textbook: New Biology: For Engineers and Computer Scientists(Pearson Education, Inc., 2004)
- Computer Programming (JAVA) (Spring 2004)
Textbook: Savitch, W., Java: An Introduction to Computer Science and Programming, Prentice Hall, 1999.
Related Courses: Spring 2002, Fall 2001, Spring 2001
- Artificial Intelligence (Fall 2004)
Textbook: Artificial Intelligence: A New Synthesis, Nils J. Nilsson, Morgan Kaufmann, 1998. Related Courses:
Spring 2001
- Data Structures (1997-2000)
Textbook: Fundamentals of Data Structures in C++, E. Horowitz, S. Sahni, and D. Mehta, Freeman and Company, 1995.
- Computer Practice (Unix) (1997-1999)
Textbook: A Practical Guide to the UNIX SYSTEM(SunOS and BSD), 3rd ed., Mark G.Sobell, Addison-Wesley, 1995.
- Introduction to Computers (1997-2002)
Textbook: Computers: Tools for an Information Age, Sixth Edition, H. L. Capron, Addison-Wesley, 2000
-
KSCI Symposium on Cognition and Artificial Intelligence,
June 27, 2012.
-
KSCI Winter School on Pattern Recognition and Machine Learning,
February 23-25, 2012.
-
KSCI Symposium on Real-Life Intelligence,
July 1, 2011.
-
KSCI Symposium on Real-Life Intelligence,
December 23, 2010.
-
The Second German-Korean Workshops on Machine Learning in Life Sciences: Computational Neuroscience,
Bernstein Center for Computational Neuroscience Berlin (BCCNB), February 2-3, 2010.
-
Cognitive Machines: Convergence of Biological and Physical Intelligence,
The 4th Forum of SNU Global Research Frontiership, November 20, 2009.
-
Áö´É-¾ð¾î-ºñÁ¯-¹ÙÀÌ¿À ¿¬ÇÕ Æ©Å丮¾ó (ILVB-2009),
Slides presented at CBIT & BI Tutorial, July 3, 2009.
-
Áö´É-¾ð¾î-ºñÁ¯-¹ÙÀÌ¿À ¿¬ÇÕ Æ©Å丮¾ó (ILVB-2008),
Slides presented at CBIT & BI Tutorial, July 2, 2008.
-
The Korean-Russian Workshops on Data Mining,
Slides presented at CBIT & BI Tutorial, May 27, 2008.
-
The First German-Korean Workshop on Machine Learning in Life Sciences,
Slides presented at CBIT & BI Tutorial, August 29-30, 2007.
-
Áö´É-¾ð¾î-ºñÁ¯-¹ÙÀÌ¿À ¿¬ÇÕ ¿öÅ©¼¥ (ILVB-2006),
Slides presented at CBIT & BI Tutorial, June 23, 2006.
-
±â°èÇнÀ ¹× ÀÀ¿ë (ILVB-2005),
Slides presented at CBIT & BI Tutorial, April 16, 2005.
-
Tutorial: Machine Learning for Biological Data Mining,
Slides presented at CBIT & BI Tutorial, November 23, 2002.
-
Bayesian Networks for Gene-Drug Dependency Analysis,
Tutorial presented at Yonsei Cancer Center, September 28, 2001.
-
Bioinformatics and Biocomputing,
Tutorial presented at Inter-university Semiconductor Research Center, July 11, 2001.
-
Bioinformation Technology (BIT) and Biointelligence (BI),
Tutorial presented at 2001 Spring Conference of Korea Information Science Society (KISS), April 28, 2001.
-
Machine Learning for Biological Data Mining,
Tutorial presented at ETRI, March 6, 2001.
-
Learning Graphical Models for DNA Chip Data Mining,
Tutorial presented at
The International Symposium on Bioinformatics,
POSTECH, November 22-23, 2000.
-
Machine Learning in Bioinformatics,
Talk given at Speical Seminar Series on Bioinformatics, Department of Life Sciences,
City University of Seoul, October 14, 2000.
This page is maintained by Sang-Woo Lee (slee@bi.snu.ac.kr).
Last update: October 4, 2013.
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