Teaching in 2010
Lecture Group, Advanced Topics in Machine Learning, Kyoto U. (Fall 2010)
12/09 13:00  14:30, Basement seminar room, Bld. 10, O. Bousquet, S. Boucheron, and G. Lugosi. Introduction to statistical learning theory. Advanced Lectures on Machine Learning, pages 169–207, 2004.
12/16 13:00  14:30, Basement seminar room, Bld. 10, C. Sutton and A. McCallum. An Introduction to Conditional Random Fields for Relational Learning. Introduction to statistical relational learning, pages 93–127, 2007.
01/06 16:30  18:00, Basement seminar room, Bld. 10, Y.W. Teh, M.I. Jordan, M.J. Beal, and D.M. Blei. Hierarchical dirichlet processes. Journal of the American Statistical Association, 101(476):1566–1581, 2006.
01/13 13:00  14:30, Room 206, Integrated Research Bld., I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun. Large margin methods for structured and interdependent output variables. Journal of Machine Learning Research, 6(2):1453, 2006.
01/27 13:00  14:30, Basement seminar room, Bld. 10, TBA
02/10 13:00  14:30, Room 107 of Bld. No. 2, TBA
Email me if you need pdf copies of the papers.
Introduction to Information Sciences, Kyoto U. (Fall 2010)
The following lectures are intended for graduate students with little or no background in computer science.
Evaluation for the course:
30% attendance (5% per missed class) & 70% assignments, split 50/50 between my assignments and Professor Liang’s assignments
Vietnam National University @ Hochiminh, Optimization and Kernel Methods (06/2010)
EPAT ML school, Kernel Methods (05/2010)
