| Topic | Subtopic | Papers |
|---|---|---|
| Supervised Learning | Boosting | Robert E. Schapire. The boosting approach to machine learning: An overview. In MSRI Workshop on Nonlinear Estimation and Classification, 2002. Yoav Freund and Robert E. Schapire. Experiments with a new boosting algorithm. Machine Learning: Proceedings of the Thirteenth International Conference, pages 148-156, 1996. Robert E. Schapire, Yoav Freund, Peter Bartlett, and Wee Sun Lee. Boosting the margin: A new explanation for the effectiveness of voting methods. The Annals of Statistics, 26(5):1651-1686, 1998. |
| Support Vector Machines | Christopher J.C. Burges. A Tutorial on Support Vector Machines for Pattern Recognition. 1998 | |
| Unsupervised Learning | Principal Component Analysis | Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller. Kernel Principal Component Analysis. In Advances in Kernel Methods: Support Vector Learning, edited by Bernhard Schölkopf, Christopher J.C. Burges, and Alexander J. Smola, 1999. | Independent Component Analysis | A. Bell and T.J. Sejnowski. An Information-Maximization Approach to Blind Separation and Blind Deconvolution. Neural Computation, 7:1129-1159, 1995. Erik Learned-Miller and John Fisher. ICA Using Spacings Estimates of Entropy. Journal of Machine Learning Research, 4:1271--1295, 2003. |
| Clustering |
Jon Kleinberg. An Impossibility Theorem for Clustering. NIPS 2002. Andrew Y. Ng, Michael I. Jordan, Yair Weiss. On Spectral Clustering: Analysis and and algorithm. NIPS 2001. Francis R. Bach and Michael I. Jordan. Learning Spectral Clustering. TR UCB/CSD-03-1249, UC Berkeley, Dept of CS, June 2003. Eamonn Keogh, Stefano Lonardi, and Chotirat Ann RatanamahatanaTowards Parameter-Free Data Mining SIGKDD, 2004. | |
| Semi-Supervised | Xiaojin Zhu, Zoubin Ghahramani, and John Lafferty, Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions. ICML, 2003. | |
| Reinforcement Learning | MDP | TBD |
| POMDP |
Michael Lederman Littman. Algorithms for Sequential Decision Making. Ph.D. disseration and TR CS-96-09, Brown University, Dept of CS, March 1996. (selected portions) Zhengzhu Feng and Shlomo Zilberstein. Region-Based Incremental Pruning for POMDPs. UAI 2004. Nicholas Roy and Geoffrey Gordon. Exponential Family PCA for Belief Compression in POMDPs. NIPS 2002. | |
| Density Estimation/Inference | Bayesian Networks | TDB |
| Dynamic Systems |
K. Murphy. Filtering, Smoothing, and the Junction Tree Algorithm. Tech Report 1998. M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp. A Tutorial on Particle Filters for On-line Non-linear/Non-Gaussian Bayesian Tracking. IEEE Transactions on Signal Processing. 50(2), 174-188. 2002. Xavier Boyen and Daphne Koller. Exploiting the Architecture of Dynamic Systems. AAAI 1999. Arnaud Doucet, Nando de Freitas, and Neil Gordon. An Introduction to Sequential Monte Carlo Methods. In Sequential Monte Carlo Methods in Practice, ed. by Arnaud Doucet, Nando de Freitas, and Neil Gordon. 2001. Kevin Murphy and Stuart Russell. Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. UAI 2000. Michael Montemerlo, Sebastian Thrun, Daphne Koller, and Ben Wegbreit. FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem. AAAI 2002. Mark A. Paskin. Thin Junction Tree Filters for Simultaneous Localization and Mapping. NIPS 2003. Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, and Eric Wan. The Unscented Particle Filter. TR CUED/F-INFENG/TR 380, Cambridge University, Dept. of Eng. May 2000. |
| Week # | Tuesday | Thursday | ||||||
|---|---|---|---|---|---|---|---|---|
| Date | Topic | Paper(s) | Leader | Date | Topic | Paper(s) | Leader | |
| 0 | Sept 23 | Intro | N/A | Christian | ||||
| 1 | Sept 28 | Boosting (basics) | Freund & Schapire and Schapire | Titus | Sept 30 | Boosting (bounds) | Schapire et. al. and Schapire | Kin |
| 2 | Oct 5 | SVMs | Burges | Guobiao | Oct 7 | PCA | N/A | Christian |
| 3 | Oct 12 | Kernel PCA | Schölkopf et al. | Jing | Oct 14 | ICA part I | Bell and Sejnowski | Xiaopeng |
| 4 | Oct 19 | ICA part II | Learned-Miller and Fisher | Christian | Oct 21 | Spectral Clustering | Ng, Jordan, and Weiss | Ryan |
| 5 | Oct 26 | Impossibility of Clustering | Kleinberg | Matt | Oct 28 | Compression and Clustering | Keogh, Lonardi, and Ratanamahatana | Titus |
| 6 | Nov 2 | Semi-Supervised Learning | Zhu, Ghahramani, and Lafferty | Jing | Nov 4 | MDPs | Littman (intro, ch 1, ch 2) | Guobiao |
| 7 | Nov 9 | MDPs | Littman | Guobiao / Kin | Nov 11 | ---Holiday--- | ||
| 8 | Nov 16 | POMDPs | Littman (ch 6-8) | Kin | Nov 18 | POMDP planning | Roy and Gordon | Matt |
| 9 | Nov 23 | Filtering | N/A | Christian | Nov 25 | ---Holiday--- | ||
| 10 | Nov 30 | Partical Filtering | Arulampalam et al. | Xiaopeng | Dec 2 | SLAM | Montemerlo et al. | Ryan |