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» Logarithmic Regret Algorithms for Online Convex Optimization
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CORR
2011
Springer
198views Education» more  CORR 2011»
12 years 11 months ago
Decentralized Online Learning Algorithms for Opportunistic Spectrum Access
—The fundamental problem of multiple secondary users contending for opportunistic spectrum access over multiple channels in cognitive radio networks has been formulated recently ...
Yi Gai, Bhaskar Krishnamachari
COLT
2008
Springer
13 years 9 months ago
Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization
We introduce an efficient algorithm for the problem of online linear optimization in the bandit setting which achieves the optimal O ( T) regret. The setting is a natural general...
Jacob Abernethy, Elad Hazan, Alexander Rakhlin
COLT
2010
Springer
13 years 5 months ago
Learning Rotations with Little Regret
We describe online algorithms for learning a rotation from pairs of unit vectors in Rn . We show that the expected regret of our online algorithm compared to the best fixed rotati...
Elad Hazan, Satyen Kale, Manfred K. Warmuth
CVPR
2012
IEEE
11 years 10 months ago
Online robust image alignment via iterative convex optimization
In this paper we study the problem of online aligning a newly arrived image to previously well-aligned images. Inspired by recent advances in batch image alignment using low rank ...
Yi Wu, Bin Shen, Haibin Ling
CORR
2012
Springer
210views Education» more  CORR 2012»
12 years 3 months ago
Towards minimax policies for online linear optimization with bandit feedback
We address the online linear optimization problem with bandit feedback. Our contribution is twofold. First, we provide an algorithm (based on exponential weights) with a regret of...
Sébastien Bubeck, Nicolò Cesa-Bianch...