259 search results - page 7 / 52 » A Hybrid Convergent Method for Learning Probabilistic Networ... |
IJCAI
1997
13 years 9 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...
UAI
1998
13 years 9 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...
ISNN
2007
Springer
14 years 1 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...
UAI
1998
13 years 9 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...
ICML
2002
IEEE
14 years 8 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...