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» Bayesian network learning by compiling to weighted MAX-SAT
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IJCNN
2008
IEEE
14 years 3 months ago
Learning associations of conjuncted fuzzy sets for data prediction
— Fuzzy Associative Conjuncted Maps (FASCOM) is a fuzzy neural network that represents information by conjuncting fuzzy sets and associates them through a combination of unsuperv...
Hanlin Goh, Joo-Hwee Lim, Chai Quek
VLDB
2006
ACM
162views Database» more  VLDB 2006»
14 years 9 months ago
Dependency trees in sub-linear time and bounded memory
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Dan Pelleg, Andrew W. Moore
ILP
2007
Springer
14 years 3 months ago
Learning to Assign Degrees of Belief in Relational Domains
A recurrent question in the design of intelligent agents is how to assign degrees of beliefs, or subjective probabilities, to various events in a relational environment. In the sta...
Frédéric Koriche
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 9 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
PKDD
2010
Springer
148views Data Mining» more  PKDD 2010»
13 years 7 months ago
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...