171 search results - page 16 / 35 » Factorized Asymptotic Bayesian Inference for Mixture Modelin... |
154
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JMLR
2010
14 years 10 months ago
2010
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
133
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ICMCS
2009
IEEE
15 years 1 months ago
2009
IEEE
The paper presents a novel multi-view learning framework based on variational inference. We formulate the framework as a graph representation in form of graph factorization: the g...
137
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ECAI
2008
Springer
15 years 5 months ago
2008
Springer
This paper describes a novel method for explaining Bayesian network (BN) inference when the network is modeling a population of conditionally independent agents, each of which is m...
121
Voted
PKDD
2009
Springer
15 years 10 months ago
2009
Springer
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
126
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ICDM
2010
IEEE
15 years 1 months ago
2010
IEEE
In this paper, we study probabilistic modeling of heterogeneously attributed multi-dimensional arrays. The model can manage the heterogeneity by employing an individual exponential...