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JAIR
2000
152views more  JAIR 2000»
14 years 9 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
ATAL
2005
Springer
15 years 3 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
CISS
2008
IEEE
15 years 4 months ago
On sparse representations of linear operators and the approximation of matrix products
—Thus far, sparse representations have been exploited largely in the context of robustly estimating functions in a noisy environment from a few measurements. In this context, the...
Mohamed-Ali Belabbas, Patrick J. Wolfe
MLG
2007
Springer
15 years 3 months ago
Learning Graph Matching
As a fundamental problem in pattern recognition, graph matching has found a variety of applications in the field of computer vision. In graph matching, patterns are modeled as gr...
Alex J. Smola
ISBI
2007
IEEE
15 years 3 months ago
A Shape-Based Finite Impulse Response Model for Functional Brain Images
We present a new Finite Impulse Response (FIR) model for hemodynamics in functional brain images. Like other FIR models, our method permits a flexible formulation of the hemodyna...
Bing Bai, Paul B. Kantor