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» Online Learning: Beyond Regret
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ECCC
2007
180views more  ECCC 2007»
13 years 7 months ago
Adaptive Algorithms for Online Decision Problems
We study the notion of learning in an oblivious changing environment. Existing online learning algorithms which minimize regret are shown to converge to the average of all locally...
Elad Hazan, C. Seshadhri
EWRL
2008
13 years 9 months ago
Markov Decision Processes with Arbitrary Reward Processes
Abstract. We consider a control problem where the decision maker interacts with a standard Markov decision process with the exception that the reward functions vary arbitrarily ove...
Jia Yuan Yu, Shie Mannor, Nahum Shimkin
COLT
2010
Springer
13 years 5 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
PODC
2009
ACM
14 years 8 months ago
Load balancing without regret in the bulletin board model
We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing a...
Éva Tardos, Georgios Piliouras, Robert D. K...
ICML
2006
IEEE
14 years 8 months ago
Algorithms for portfolio management based on the Newton method
We experimentally study on-line investment algorithms first proposed by Agarwal and Hazan and extended by Hazan et al. which achieve almost the same wealth as the best constant-re...
Amit Agarwal, Elad Hazan, Satyen Kale, Robert E. S...