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119
Voted
ICPR
2008
IEEE
16 years 4 months ago
2008
IEEE
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
142
Voted
ICML
2000
IEEE
16 years 4 months ago
2000
IEEE
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
120
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STOC
2003
ACM
16 years 3 months ago
2003
ACM
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
130
Voted
SDM
2009
SIAM
16 years 18 days ago
2009
SIAM
We propose Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using aux...
112
Voted
ALT
2007
Springer
16 years 11 days ago
2007
Springer
Abstract. We consider the problem of learning stochastic tree languages, i.e. probability distributions over a set of trees T(F), from a sample of trees independently drawn accordi...