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114
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CP
1999
Springer
15 years 4 months ago
Rewriting Numeric Constraint Satisfaction Problems for Consistency Algorithms
Reformulating constraint satisfaction problems (CSPs) in lower arity is a common procedure when computing consistency. Lower arity CSPs are simpler to treat than high arity CSPs. ...
Claudio Lottaz
UAI
2003
15 years 1 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
JMLR
2012
13 years 3 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
108
Voted
ORL
2008
63views more  ORL 2008»
15 years 16 days ago
The inequality-satisfiability problem
We define a generalized variant of the satisfiability problem (SAT) where each "clause" is an or-list of inequalities in n variables. The inequality satisfiability probl...
Dorit S. Hochbaum, Erick Moreno-Centeno
98
Voted
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 1 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...