4947 search results - page 225 / 990 » Learning Module Networks |
122
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SODA
2001
ACM
15 years 4 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
127
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UAI
1993
15 years 4 months ago
1993
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
123
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JETAI
1998
15 years 3 months ago
1998
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
128
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JPDC
2011
14 years 6 months ago
2011
: One important problem which may arise in designing a deployment strategy for a wireless sensor network is how to deploy a specific number of sensor nodes throughout an unknown ne...
190
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MLG
2007
Springer
15 years 9 months ago
2007
Springer
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...