Optimization, learning, and games with predictable sequences

Advances in Neural Information Processing Systems

Volumn , Issue , 2013, Pages

  Rakhlin, Alexander ^a   Sridharan, Karthik ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; MIRRORS;

MATRIX GAME; MAX-FLOW PROBLEM; MINIMAX; OFF-LINE OPTIMIZATION; ONLINE LEARNING ALGORITHMS; PARTIAL INFORMATION; SADDLE POINT; SIMPLE ALGORITHM;

OPTIMIZATION;

EID: 84898930412     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. S. Arora, E. Hazan, and S. Kale. The multiplicative weights update method: A meta-algorithm and applications. Theory of Computing, 8(1):121-164, 2012.
2. P. Auer, N. Cesa-Bianchi, and C. Gentile. Adaptive and self-confident on-line learning algorithms. Journal of Computer and System Sciences, 64(1):48-75, 2002.
3. N. Cesa-Bianchi and G. Lugosi. Prediction, Learning, and Games. Cambridge University Press, 2006.
4. C.-K. Chiang, T. Yang, C.-J. Lee, M. Mahdavi, C.-J. Lu, R. Jin, and S. Zhu. Online optimization with gradual variations. In COLT, 2012.
5. P. Christiano, J. A Kelner, A. Madry, D. A. Spielman, and S.-H. Teng. Electrical flows, laplacian systems, and faster approximation of maximum flow in undirected graphs. In Proceedings of the 43rd annual ACM symposium on Theory of computing, pages 273-282. ACM, 2011.
6. C. Daskalakis, A. Deckelbaum, and A. Kim. Near-optimal no-regret al.gorithms for zerosum games. In Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, pages 235-254. SIAM, 2011.
7. Y. Freund and R. Schapire. Adaptive game playing using multiplicative weights. Games and Economic Behavior, 29(1):79-103, 1999.
8. A. Goldberg and S. Rao. Beyond the flow decomposition barrier. Journal of the ACM (JACM), 45(5):783-797, 1998.
9. A. Nemirovski. Prox-method with rate of convergence O(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems. SIAM Journal on Optimization, 15(1):229-251, 2004.
10. Y. Nesterov. Smooth minimization of non-smooth functions. Mathematical Programming, 103(1):127-152, 2005.
11. A. Rakhlin and K. Sridharan. Online learning with predictable sequences. In Proceedings of the 26th Annual Conference on Learning Theory (COLT), 2013.