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» Bayesian network learning by compiling to weighted MAX-SAT
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IJCNN
2008
IEEE
16 years 3 days 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»
16 years 5 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
15 years 12 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»
16 years 6 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»
15 years 4 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...