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ML
2002
ACM
143views Machine Learning» more  ML 2002»
15 years 3 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
TEC
2008
135views more  TEC 2008»
15 years 3 months ago
Evolving Output Codes for Multiclass Problems
In this paper, we propose an evolutionary approach to the design of output codes for multiclass pattern recognition problems. This approach has the advantage of taking into account...
Nicolás García-Pedrajas, Colin Fyfe
159
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COLT
2010
Springer
15 years 1 months ago
Open Loop Optimistic Planning
We consider the problem of planning in a stochastic and discounted environment with a limited numerical budget. More precisely, we investigate strategies exploring the set of poss...
Sébastien Bubeck, Rémi Munos
COLT
2010
Springer
15 years 1 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
COMBINATORICA
2010
15 years 1 months ago
A randomized embedding algorithm for trees
In this paper, we propose a simple and natural randomized algorithm to embed a tree T in a given graph G. The algorithm can be viewed as a "self-avoiding tree-indexed random ...
Benny Sudakov, Jan Vondrák