4947 search results - page 224 / 990 » Learning Module Networks |
118
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ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
117
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ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
153
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ICCV
2007
IEEE
16 years 5 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 ...
120
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EVOW
2008
Springer
15 years 5 months ago
2008
Springer
In many cases what matters is not whether a false discovery is made or not but the expected proportion of false discoveries among all the discoveries made, i.e. the so-called false...
125
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ICML
2005
IEEE
16 years 4 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...