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125
Voted
NIPS
2004
15 years 3 months ago
2004
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
153
Voted
JMLR
2012
13 years 5 months ago
2012
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
107
Voted
ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
157
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BMCBI
2010
14 years 9 months ago
2010
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
125
Voted
ICRA
2008
IEEE
15 years 9 months ago
2008
IEEE
— This paper proposes and experimentally validates a Bayesian network model of a range finder adapted to dynamic environments. The modeling rigorously explains all model assumpt...