2103 search results - page 19 / 421 » Approximate Learning of Dynamic Models |
CORR
2010
Springer
15 years 1 months ago
2010
Springer
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
104
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NIPS
1998
15 years 3 months ago
1998
We present Monte-Carlo generalized EM equations for learning in nonlinear state space models. The dif
100
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FUZZIEEE
2007
IEEE
15 years 8 months ago
2007
IEEE
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
129
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JMLR
2010
2010
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
14 years 8 months ago
The presence of asymmetry in the misclassification costs or class prevalences is a common occurrence in the pattern classification domain. While much interest has been devoted to ...
171
Voted
AI
1998
Springer
15 years 1 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...