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» On the Convergence of Bound Optimization Algorithms
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ICML
2009
IEEE
14 years 9 months ago
Near-Bayesian exploration in polynomial time
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
J. Zico Kolter, Andrew Y. Ng
IPL
2006
89views more  IPL 2006»
13 years 9 months ago
Adaptive general perfectly periodic scheduling
We propose an adaptive algorithm Adaptmin to create perfectly periodic schedules. A perfectly periodic schedule schedules a client regularly after a predefined amount of time known...
Shailesh Patil, Vijay K. Garg
PLDI
2012
ACM
11 years 11 months ago
Fast and precise hybrid type inference for JavaScript
JavaScript performance is often bound by its dynamically typed nature. Compilers do not have access to static type information, making generation of efficient, type-specialized m...
Brian Hackett, Shu-yu Guo
CVPR
2012
IEEE
11 years 11 months ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis
ATAL
2006
Springer
14 years 21 days ago
Learning to commit in repeated games
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
Stéphane Airiau, Sandip Sen