4930 search results - page 31 / 986 » Learning minimal abstractions |
107
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ICML
1994
IEEE
15 years 4 months ago
1994
IEEE
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
88
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CAV
2005
Springer
15 years 6 months ago
2005
Springer
Abstract. We address the issue of efficiently automating assume-guarantee reasoning for simulation conformance between finite state systems and specifications. We focus on a non...
GECCO
2010
Springer
15 years 5 months ago
2010
Springer
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...
87
Voted
ICANN
2003
Springer
15 years 5 months ago
2003
Springer
Abstract. This paper proposes a general approach named ExpectationMiniMax (EMM) for clustering analysis without knowing the cluster number. It describes the contrast function of Ex...
95
Voted
LICS
2005
IEEE
15 years 6 months ago
2005
IEEE
Three-valued models, in which properties of a system are either true, false or unknown, have recently been advocated as a better representation for reactive program abstractions g...