606 search results - page 80 / 122 » Combinatorial Markov Random Fields |
UAI
2004
15 years 2 months ago
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
118
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UAI
2004
15 years 2 months ago
2004
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
121
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
125
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ICCV
2007
IEEE
16 years 2 months ago
2007
IEEE
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
101
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CIKM
2008
Springer
15 years 2 months ago
2008
Springer
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...