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ICML
2005
IEEE
14 years 9 months ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
TFS
2011
239views Education» more  TFS 2011»
13 years 3 months ago
Systems Control With Generalized Probabilistic Fuzzy-Reinforcement Learning
—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
William M. Hinojosa, Samia Nefti, Uzay Kaymak
JMLR
2010
123views more  JMLR 2010»
13 years 3 months ago
Inductive Principles for Restricted Boltzmann Machine Learning
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
Benjamin Marlin, Kevin Swersky, Bo Chen, Nando de ...
ATAL
2009
Springer
14 years 3 months ago
Transfer via soft homomorphisms
The field of transfer learning aims to speed up learning across multiple related tasks by transferring knowledge between source and target tasks. Past work has shown that when th...
Jonathan Sorg, Satinder Singh
ECML
2007
Springer
14 years 24 days ago
Modeling Highway Traffic Volumes
Most traffic management and optimization tasks, such as accident detection or optimal vehicle routing, require an ability to adequately model, reason about and predict irregular an...
Tomás Singliar, Milos Hauskrecht