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JAIR
2000
152views more  JAIR 2000»
13 years 8 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
PRL
2000
182views more  PRL 2000»
13 years 8 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
CEC
2010
IEEE
13 years 14 days ago
A hybrid genetic algorithm for rescue path planning in uncertain adversarial environment
— Efficient vehicle path planning in hostile environment to carry out rescue or tactical logistic missions remains very challenging. Most approaches reported so far relies on key...
Jean Berger, Khaled Jabeur, Abdeslem Boukhtouta, A...
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 10 months ago
ASAGA: an adaptive surrogate-assisted genetic algorithm
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
Liang Shi, Khaled Rasheed
ICML
2009
IEEE
14 years 9 months ago
Sparse Gaussian graphical models with unknown block structure
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
Benjamin M. Marlin, Kevin P. Murphy