SCAI Seminar/Lecture Notes Available Online

Seminar Slides

Machine Learning
- Machine Learning Seminar for Rookies
  Textbook: Machine Learning, Tom Mitchell, McGraw Hill, 1998.
- Pattern Recognition and Machine Learning
  Textbook: Pattern Recognition and Machine Learning, Christopher M. Bishop,Springer, 2006.
Bioinformatics
- Bioinformatics Seminar
  Textbook: Computational Methods in Molecular Biology, Steven L. Salzberg(Editor), et al, 1999.
Biocomputing
- Molecular Evolutionary Computing Seminar
- Papers in Science and Nature
Probabilistic Learning
- Bayesian Netwoks
- Latent Variable Models
- Instance Selection and Construction
  Textbook: Instance Selection and Construction for Data Mining, Huan Liu and Hiroshi Motoda, 2001

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.

Lecture Notes

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

Tutorial Slides

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.
��-��-��-��̿� �� Ʃ�丮�� (ILVB-2009), Slides presented at CBIT & BI Tutorial, July 3, 2009.
��-��-��-��̿� �� Ʃ�丮�� (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.
��-��-��-��̿� �� ũ�� (ILVB-2006), Slides presented at CBIT & BI Tutorial, June 23, 2006.
��н� �� (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.