1753 search results - page 64 / 351 » State Machines |
145
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ICML
2008
IEEE
16 years 7 months ago
2008
IEEE
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
139
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ECML
2006
Springer
15 years 10 months ago
2006
Springer
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
157
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CSCLP
2006
Springer
15 years 10 months ago
2006
Springer
Abstract. Traditional resources in scheduling are simple machines where a capacity is the main restriction. However, in practice there frequently appear resources with more complex...
179
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ASWEC
2005
IEEE
15 years 11 months ago
2005
IEEE
Starting with a UML specification that captures the underlying functionality of some given Java-based concurrent system, we describe a systematic way to construct, from this speci...
293
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NEUROSCIENCE
2001
Springer
15 years 10 months ago
2001
Springer
Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...