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CS7941: Online Learning

Time: Fridays, 2-3:20

Location: MEB 3105, except as noted

Topic: Online learning

Participants

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	[xxx] by xxx	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

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.

Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, Robert Schapire: The Nonstochastic Multiarmed Bandit Problem, SIAM J. Comput. 32(1): 48-77 (2002).

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.