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COLT
2005
Springer
16 years 6 days ago
Learning Convex Combinations of Continuously Parameterized Basic Kernels
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
ECML
2005
Springer
16 years 6 days ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
ECML
2005
Springer
16 years 6 days ago
Active Learning for Probability Estimation Using Jensen-Shannon Divergence
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
Prem Melville, Stewart M. Yang, Maytal Saar-Tsecha...
ICML
1994
IEEE
15 years 10 months ago
Markov Games as a Framework for Multi-Agent Reinforcement Learning
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
Michael L. Littman
SAB
2010
Springer
150views Optimization» more  SAB 2010»
15 years 4 months ago
Internal Models in the Cerebellum: A Coupling Scheme for Online and Offline Learning in Procedural Tasks
The cerebellum plays a major role in motor control. It is thought to mediate the acquisition of forward and inverse internal models of the bodyenvironment interaction [1]. In this ...
Jean-Baptiste Passot, Niceto Luque, Angelo Arleo