204 search results - page 19 / 41 » Learning locally minimax optimal Bayesian networks |
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AI
1998
Springer
14 years 9 months ago
1998
Springer
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
ICCV
2005
IEEE
15 years 11 months ago
2005
IEEE
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
AUSAI
2004
Springer
15 years 2 months ago
2004
Springer
We describe an Ant Colony Optimization (ACO) algorithm, ANT-MPE, for the most probable explanation problem in Bayesian network inference. After tuning its parameters settings, we c...
JMLR
2010
14 years 4 months ago
2010
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
ICANNGA
2009
Springer
15 years 4 months ago
2009
Springer
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...