MLRG/fall09
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Revision as of 19:40, 11 September 2009
Contents |
CS7941: Online Learning
Time: Fridays, 2-3:20
Location: MEB 3105, except as noted
Topic: Online learning
Participants
- Hal Daumé III, Assistant Professor, School of Computing
- Seth Juarez, PhD Student, School of Computing
- Piyush Rai, PhD Student, School of Computing
- Youngjun Kim, PhD Student, School of Computing
- Arvind Agarwal, PhD Student, School of Computing
- Jiarong Jiang, PhD Student, School of Computing
- Avishek Saha, PhD Student, School of Computing
- Amit Goyal, PhD Student, School of Computing
- Ruihong Huang, PhD Student, School of Computing
- Ramesh Pinnamaneni, MS Student, School of Computing
Schedule
| Date | Papers | Presenter |
|---|---|---|
| Sep 04 | Online Learning Survey by Avrim Blum | Hal |
| Sep 11 | Learning Quickly when Irrelevant Attributes Abound: A New Linear-threshold Algorithm by Nick Littlestone | Sandeep and Shuying |
| Sep 18 | [xxx] by xxx | |
| Sep 25 | Efficient algorithms for the online decision problem by Adam Kalai and Santosh Vempala | Seth |
| Oct 02 | Online convex programming and generalized infinitesimal gradient ascent by M. Zinkevich | Jiarong |
| Oct 23 | Confidence-Weighted Linear Classification by Mark Dredze, Koby Crammer and Fernando Pereira | Amit |
| Oct 30 | Step Size-Adapted Online Support Vector Learning by Karatzoglou, Vishwanathan, Schraudolph, and Smola | Ramesh |
| Nov 06 | A New Perspective on an Old Perceptron Algorithm by Shai Shalev-Shwartz and Yoram Singer | Youngjun and anyone who wants to be his team |
| Nov 13 | Data-Driven Online to Batch Conversions by Ofer Dekel and Yoram Singer | Ruihong and Adam |
| Nov 20 | [some bandit paper] by [some bandit paper author(s)] - kindly leave the bandit papers for me :) | Avishek |
| Dec 04 | [xxx] by xxx | |
| Dec 11 | [xxx] by xxx |
Possible Papers
- Nick Littlestone, Learning Quickly when Irrelevant Attributes Abound: A New Linear-threshold Algorithm. Machine Learning 2:285--318, 1987. (The version pointed to here is the tech report UCSC-CRL-87-28.)
- Littlestone and Warmuth, The Weighted Majority Algorithm. Information and Computation 108(2):212-261, 1994.
- Nicolo Cesa-Bianchi, Yoav Freund, David Haussler, David Helmbold, Robert Schapire, and Manfred Warmuth, How to use expert advice, Journal of the ACM, 44(3):427-485, May 1997.
- Yoav Freund and Robert Schapire, Adaptive game playing using multiplicative weights, Games and Economic Behavior, 29:79-103, 1999.
- Adam Kalai and Santosh Vempala, Efficient algorithms for the online decision problem, COLT '03.
- Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, Robert Schapire: The Nonstochastic Multiarmed Bandit Problem, SIAM J. Comput. 32(1): 48-77 (2002).
- Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary. By Brendan McMahan and Avrim Blum. COLT '04.
- Abie Flaxman, Adam Tauman Kalai, and Brendan McMahan. Online Convex Optimization in the Bandit Setting: Gradient Descent Without a Gradient. In Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 385-394, 2005.
- M. Zinkevich. Online convex programming and generalized infinitesimal gradient ascent. In Twentieth International Conference on Machine Learning, 2003.
- Online Passive-Aggressive Algorithms. Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer
- Confidence-Weighted Linear Classification Mark Dredze, Koby Crammer and Fernando Pereira. Proceedings of the 25th International Conference on Machine Learning (ICML), 2008
- John Langford, Lihong Li and Tong Zhang. Sparse Online Learning via Truncated Gradient. Journal of Machine Learning Research, 10:777-801, 2009.
- Alexandros Karatzoglou, S.V.N. Vishwanathan, Nicol N. Schraudolph, and Alex J. Smola. Step Size-Adapted Online Support Vector Learning. In Proc. 8th Intl. Symp. Signal Processing & Applications, IEEE, 2005.
- Risk-Sensitive Online Learning. With E. Even-Dar and J. Wortman. ALT 2006.
- Ofer Dekel and Yoram Singer. Data-Driven Online to Batch Conversions NIPS*05
- Shai Shalev-Shwartz and Yoram Singer. A New Perspective on an Old Perceptron Algorithm. COLT*05
Paper Summaries
Past Semesters
- Summer 2009 (Assorted Topics)
- Spring 2009 (Learning Theory)
- Fall 2008 (Graphical Models)
- Summer 2008 (Multitask Learning)
- Spring 2008 (Kernel Methods)
- Fall 2007 (Unsupervised Bayes)
- Summer 2007 (Manifolds)
