4930 search results - page 349 / 986 » Learning minimal abstractions |
193
Voted
PKDD
2010
Springer
15 years 5 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
214
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ECAI
2010
Springer
15 years 4 months ago
2010
Springer
Abstract. Statistical relational models, such as Markov logic networks, seek to compactly describe properties of relational domains by representing general principles about objects...
239
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AROBOTS
2011
15 years 1 months ago
2011
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
169
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TCAD
2010
15 years 1 months ago
2010
Abstract--Functional verification is one of the major bottlenecks in system-on-chip design due to the combined effects of increasing complexity and lack of automated techniques for...
218
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TNN
2010
15 years 1 months ago
2010
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...