 Interdisciplinary Program in Cognitive Science, Seoul National University
 Instructor: Dr. Joon Shik Kim (Room: 3023141, Email: jskim@bi.snu.ac.kr, Tel: 8801847, H.P.: 01028380324)
 TA: ChungYeon Lee (Room: 3023141, Email: cylee@bi.snu.ac.kr, Tel: 8801847)
 Classroom: 142071
 Time: Friday 09:0012:00
 Objectives
 Mathematical and statistical modeling of intelligence
 Study of an information processing system based on the masterpiece papers in early days
 Study of inference algorithms of Markov chain Monte Carlo (MCMC)
 Text book
 Unsupervised Learning: Foundations of Neural Computation, edited by Geoffrey Hinton and Terrence J. Sejnowski, The MIT Press, 1999
 Evaluation
 Paper presentation (20%)
 Research presentation I (15%)
 Research presentation II (15%)
 Report of a term project (30%)
 Participation in discussion (20%)
 Announcement
 Presentation will be evaluated by other students
 A term project
 The project consists of performing a cognitive science experiment and writing a final report
 Main reference for a project will be presented at the paper presentation class
 References
 Computing machinery and intelligence, AM Turing, Mind, 59(236): 433460, 1950.
 Preliminary discussion of the logical design of an electronic computing instrument, AW Burks, HH Goldstine, and J von Neumann, Papers of John von Neumann on computing and computer theory: MIT press, 97142, 1987.
 A theory for archicortex, D Marr, Philosophical transactions of the royal society of London, 262: 381, 1971.
 Theory of communication, CE Shannon, ACM mobile communications review, 5(1): 355, 2001.
 A global minimization algorithm based on a geodesic of a Lagrangian formulation of Newtonian dynamics, JS Kim, JC Kim, J O, and BT Zhang, Neural Processing Letters, 26(2): 121131, 2007.
 Markov chain sampling methods for Drichlet process mixture models, RM Neal, Journal of computational and graphical statistics, 9(2): 249265, 2000.
 Hierarchical Dirichlet processes, YW Teh, MI Jordan, MJ Beal, DM Blei, Journal of the American statistical association, 101(476): 15661581, 2005.
 Z Ghahramani, TL Griffiths, and P Sollich, Bayesian nonparametric latent feature model, proc. Valencia / ISBA 8th world meeting on Bayesian statistics, June 1st6th, 2006.
 NL Roux and Y Bengio, Representational power of restricted Boltzmann machines and deep belief networks, Neural Computation, 20: 16311649, 2008.
 An evolutionary Monte Carlo algorithm for predicting DNA hybridization, JS Kim, JW Lee, YK Noh, JY Park, DY Lee, KA Yang, YG Chai, JC Kim, and BT Zhang, Biosystems, 91(1):6975, 2008.
 Schedule
Date 
Paper 
Speaker 
Slides 
9.2 
Paper written by Turing (Ref. [1]) 
Joon Shik Kim 

9.9 
Paper written by Neumann (Ref. [2]) 
Joon Shik Kim 

9.16 
Paper written by Marr (Ref. [3]) 
Joon Shik Kim 

9.23 
Paper written by Shannon (Ref. [4]) 
Joon Shik Kim 

9.30 
Geodesic of a Lagrangian (Ref. [4]) 
Joon Shik Kim 

10.7 
Paper Presentation 
Students 

10.14 
Markov chain sampling (Ref. [6]) 
Joon Shik Kim 

10.21 
Hierachical Dirichlet process (Ref. [7]) 
Joon Shik Kim 

10.28 
Indian buffet process (Ref. [8]) 
Joon Shik Kim 

11.4 
Research Presentation I 
Students 

11.11 
Restricted Bolzmann machine (Ref. [9]) 
Joon Shik Kim 

11.18 
DNA computing (Ref. [10]) 
Joon Shik Kim 

11.25 
Research presentation II 
Students 

12.2 
Due day of the final report 


