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ICML
2010
IEEE
15 years 7 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
ISCI
2006
96views more  ISCI 2006»
15 years 6 months ago
A comparison of classification accuracy of four genetic programming-evolved intelligent structures
We investigate the effectiveness of GP-generated intelligent structures in classification tasks. Specifically, we present and use four context-free grammars to describe (1) decisi...
Athanasios Tsakonas
JMLR
2006
113views more  JMLR 2006»
15 years 6 months ago
Learning the Structure of Linear Latent Variable Models
We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
Ricardo Silva, Richard Scheines, Clark Glymour, Pe...
153
Voted
EOR
2007
90views more  EOR 2007»
15 years 6 months ago
Structural models in consumer credit
We propose a structural credit risk model for consumer lending using option theory and the concept of the value of the consumer’s reputation. Using Brazilian empirical data and ...
Fabio Wendling Muniz de Andrade, Lyn C. Thomas
NAR
2006
164views more  NAR 2006»
15 years 6 months ago
FISH - family identification of sequence homologues using structure anchored hidden Markov models
The FISH server is highly accurate in identifying the family membership of domains in a query protein sequence, even in the case of very low sequence identities to known homologue...
Jeanette Tångrot, Lixiao Wang, Bo Kågs...