259 search results - page 7 / 52 » A Hybrid Convergent Method for Learning Probabilistic Networ... |
127
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IJCAI
1997
15 years 5 months ago
1997
Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ m...
171
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UAI
1998
15 years 5 months ago
1998
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
145
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ISNN
2007
Springer
15 years 10 months ago
2007
Springer
In recent years, many efforts have been put in applying the concept of reconfigurable computing to neural networks. In our previous pursuits, an innovative self-organizing learning...
123
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UAI
1998
15 years 5 months ago
1998
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
125
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ICML
2002
IEEE
16 years 5 months ago
2002
IEEE
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...