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NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 7 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
ICML
2010
IEEE
13 years 8 months ago
Feature Selection as a One-Player Game
This paper formalizes Feature Selection as a Reinforcement Learning problem, leading to a provably optimal though intractable selection policy. As a second contribution, this pape...
Romaric Gaudel, Michèle Sebag
JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
A Convergent Online Single Time Scale Actor Critic Algorithm
Actor-Critic based approaches were among the first to address reinforcement learning in a general setting. Recently, these algorithms have gained renewed interest due to their gen...
Dotan Di Castro, Ron Meir
ICML
2009
IEEE
14 years 8 months ago
Regularization and feature selection in least-squares temporal difference learning
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
J. Zico Kolter, Andrew Y. Ng
ECAI
2006
Springer
13 years 11 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani