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» Learning Markov Network Structure with Decision Trees
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ICMLA
2007
13 years 10 months ago
Learning bayesian networks consistent with the optimal branching
We introduce a polynomial-time algorithm to learn Bayesian networks whose structure is restricted to nodes with in-degree at most k and to edges consistent with the optimal branch...
Alexandra M. Carvalho, Arlindo L. Oliveira
ICML
2007
IEEE
14 years 9 months ago
A recursive method for discriminative mixture learning
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
Minyoung Kim, Vladimir Pavlovic
ADC
2003
Springer
115views Database» more  ADC 2003»
14 years 14 days ago
Document Classification via Structure Synopses
Information available in the Internet is frequently supplied simply as plain ascii text, structured according to orthographic and semantic conventions. Traditional document classi...
Liping Ma, John Shepherd, Anh Nguyen
AAAI
2012
11 years 11 months ago
POMDPs Make Better Hackers: Accounting for Uncertainty in Penetration Testing
Penetration Testing is a methodology for assessing network security, by generating and executing possible hacking attacks. Doing so automatically allows for regular and systematic...
Carlos Sarraute, Olivier Buffet, Jörg Hoffman...
EMNLP
2004
13 years 10 months ago
Induction of Greedy Controllers for Deterministic Treebank Parsers
Most statistical parsers have used the grammar induction approach, in which a stochastic grammar is induced from a treebank. An alternative approach is to induce a controller for ...
Tom Kalt