869 search results - page 17 / 174 » Max-Margin Markov Networks |
ICDM
2010
IEEE
14 years 7 months ago
2010
IEEE
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
ICML
2009
IEEE
15 years 10 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...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
CSSE
2008
IEEE
15 years 4 months ago
2008
IEEE
—Risk assessment is a very important tool to acquire a present and future security status of the network information system. Many risk assessment approaches consider the present ...