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IR
2010
15 years 2 months ago
A general approximation framework for direct optimization of information retrieval measures
Recently direct optimization of information retrieval (IR) measures becomes a new trend in learning to rank. Several methods have been proposed and the effectiveness of them has ...
Tao Qin, Tie-Yan Liu, Hang Li
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
15 years 2 months ago
Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
CDC
2010
IEEE
136views Control Systems» more  CDC 2010»
14 years 11 months ago
Pathologies of temporal difference methods in approximate dynamic programming
Approximate policy iteration methods based on temporal differences are popular in practice, and have been tested extensively, dating to the early nineties, but the associated conve...
Dimitri P. Bertsekas
JAIR
2011
187views more  JAIR 2011»
14 years 11 months ago
A Monte-Carlo AIXI Approximation
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
ICML
2009
IEEE
15 years 11 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider