Computational Cognition and Learning Lab

Machine Learning Seminar (Spring 2005)

Dates	Topics	Papers
1/12	Introduction and Organization
1/19	EM Mixture Models	Supervised learning from incomplete data via an EM approach (1994) A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models (1998) A Graphical Illustration of the EM Algorithm (1997) SMEM Algorithm for Mixture Models (1999)
1/26	PCA Eigenface Kernel PCA	Eigenfaces for recognition. Matthew Turk and Alex Pentland (1991) Nonlinear Component Analysis as a Kernel Eigenvalue Problem. B. Scholkopf, A.J. Smola, and K.-R. Muller. (1998) A Kernel PCA Method for Superior Word Sense Disambiguation. D. Wu, W. Su and M. Carpuat (2004)
2/02	no meeting
2/09	Latent Semantic Analysis Probabilistic Latent Semantic Analysis	Indexing by Latent Semantic Analysis. Scott Deerwester, Susan T. Dumais, George W. Furnas, Thomas K. Landauer, Richard Harshman (1990) Probabilistic Latent Semantic Analysis T. Hofmann (1999)
2/16	Discussion	Text Classification from Labeled and Unlabeled Documents using EM (1999) Mixture models of categorization. Yves Rosseel (2002) Sampling Methods for Unsupervised Learning (2004) Finding scientific topics. Thomas L. Griffiths and Mark Steyvers (2004)
2/23	ICA/Fingerprint Recognition Nonlinear dimension reduction	Tom Busey: ICA/Fingerprint A global geometric framework for nonlinear dimensionality reduction J. B. Tenenbaum, V. De Silva and J. C. Langford (2000). Science 290 (5500), 2319-2323 Sam T. Roweis and Lawrence K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290:2323--2326, Dec., 22 2000.
3/02	Support Vector Machine	Chapter 6 in Simon Haykin's book M. A. Hearst, B. Schvlkopf, S. Dumais, E. Osuna, and J. Platt. Trends and controversies - support vector machines. IEEE Intelligent Systems, 13(4):18-28, 1998
3/09	Dynamic programming Hidden Markov Models	L. R. Rabiner (1989). "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition," Proceedings of the IEEE, vol 77, no 2, 257--287.
3/16	spring break
3/23	Discussion	Thorsten Joachims, Transductive Inference for Text Classification using Support Vector Machines. International Conference on Machine Learning (ICML), 1999. O. Jenkins and M. Mataric. A Spatio-temporal Extension to Isomap Nonlinear Dimension Reduction. Proceedings of the Twenty-First International Conference on Machine Learning (ICML-2004) Modeling Individual and Group Actions in Meetings: a Two-Layer HMM Framework Dong Zhang, Daniel Gatica-Perez, Samy Bengio, Iain McCowan, and Guillaume Lathoud (CVPR-2004) LAFTER: A real-time lips and face tracker with facial expression recognition Nuria Oliver, Francois Berard and Alex Pentland. Pattern Recognition, vol. 33 (2000)
3/30	Co-training Co-EM	Kamal Nigam and Rayid Ghani. Analyzing the Effectiveness and Applicability of Co-training. In CIKM-2000 Rayid Ghani. Combining Labeled and Unlabeled Data for MultiClass Text Categorization Rayid Ghani. In ICML 2002 Ulf Brefeld and Tobias Scheffer. Co-EM Support Vector Learning. In ICML 2004
4/05	Bayesian Networks DBN	Kevin Murphy A Brief Introduction to Graphical Models and Bayesian Networks