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ESANN
2001
13 years 6 months ago
Transfer functions: hidden possibilities for better neural networks
Abstract. Sigmoidal or radial transfer functions do not guarantee the best generalization nor fast learning of neural networks. Families of parameterized transfer functions provide...
Wlodzislaw Duch, Norbert Jankowski
ICML
2008
IEEE
14 years 5 months ago
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
We show that linear value-function approximation is equivalent to a form of linear model approximation. We then derive a relationship between the model-approximation error and the...
Ronald Parr, Lihong Li, Gavin Taylor, Christopher ...
ICML
2009
IEEE
14 years 5 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
ICASSP
2011
IEEE
12 years 8 months ago
Feature selection based on Multiple Kernel Learning for single-channel sound source localization using the acoustic transfer fun
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work [1], we discussed the single-channel sound source localization...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
CIKM
2010
Springer
13 years 2 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan