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» Online Dynamic Value System for Machine Learning
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ICML
2005
IEEE
14 years 8 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
ICML
1998
IEEE
14 years 8 months ago
Value Function Based Production Scheduling
Production scheduling, the problem of sequentially con guring a factory to meet forecasted demands, is a critical problem throughout the manufacturing industry. The requirement of...
Jeff G. Schneider, Justin A. Boyan, Andrew W. Moor...
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
DEDS
2006
101views more  DEDS 2006»
13 years 7 months ago
Near-Optimal Online Control of Dynamic Discrete-Event Systems
A class of time-varying discrete-event systems, named dynamic discrete-event systems, is defined. The goal of this paper is to provide a method which is modular and can be applied ...
Lenko Grigorov, Karen Rudie
ICML
2003
IEEE
14 years 8 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir