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SBIA
2004
Springer
15 years 3 months ago
Heuristically Accelerated Q-Learning: A New Approach to Speed Up Reinforcement Learning
This work presents a new algorithm, called Heuristically Accelerated Q–Learning (HAQL), that allows the use of heuristics to speed up the well-known Reinforcement Learning algori...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
STOC
2003
ACM
122views Algorithms» more  STOC 2003»
15 years 10 months ago
Learning juntas
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
ECML
2004
Springer
15 years 3 months ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
CVPR
1998
IEEE
15 years 2 months ago
Minimax Entropy and Learning by Diffusion
1 A system of coupled differential equations is formulated which learns priors for modelling "preattentive" textures. It is derived from an energy functional consisting o...
Jayant Shah
COLT
2006
Springer
15 years 1 months ago
Online Multitask Learning
We study the problem of online learning of multiple tasks in parallel. On each online round, the algorithm receives an instance and makes a prediction for each one of the parallel ...
Ofer Dekel, Philip M. Long, Yoram Singer