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ICASSP
2009
IEEE
14 years 3 months ago
Map approach to learning sparse Gaussian Markov networks
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
Narges Bani Asadi, Irina Rish, Katya Scheinberg, D...
CONSTRAINTS
2008
89views more  CONSTRAINTS 2008»
13 years 9 months ago
A Reinforcement Learning Approach to Interval Constraint Propagation
When solving systems of nonlinear equations with interval constraint methods, it has often been observed that many calls to contracting operators do not participate actively to th...
Frédéric Goualard, Christophe Jerman...
CIS
2008
Springer
13 years 10 months ago
Cooperation Controlled Competitive Learning Approach for Data Clustering
Rival Penalized Competitive Learning (RPCL) and its variants can perform clustering analysis efficiently with the ability of selecting the cluster number automatically. Although t...
Tao Li, Wenjiang Pei, Shao-ping Wang, Yiu-ming Che...
KDD
2009
ACM
175views Data Mining» more  KDD 2009»
14 years 1 months ago
Multi-class protein fold recognition using large margin logic based divide and conquer learning
Inductive Logic Programming (ILP) systems have been successfully applied to solve complex problems in bioinformatics by viewing them as binary classification tasks. It remains an...
Huma Lodhi, Stephen Muggleton, Michael J. E. Stern...
KDD
1994
ACM
98views Data Mining» more  KDD 1994»
14 years 27 days ago
Rule Induction for Semantic Query Optimization
Semantic query optimization can dramatically speed up database query answering by knowledge intensive reformulation. But the problem of how to learn required semantic rules has no...
Chun-Nan Hsu, Craig A. Knoblock