602 search results - page 27 / 121 » A New Approximation Method of the Quadratic Discriminant Fun... |
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
CORR
2010
Springer
14 years 7 months ago
2010
Springer
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors a...
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ICRA
2007
IEEE
15 years 3 months ago
2007
IEEE
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
106
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ICML
2006
IEEE
2006
IEEE
Automatic basis function construction for approximate dynamic programming and reinforcement learning
15 years 3 months ago
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
ICPR
2000
IEEE
15 years 10 months ago
2000
IEEE
In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regressio...