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151
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JMLR
2010
14 years 10 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
182
Voted
CVPR
2008
IEEE
15 years 3 months ago
2008
IEEE
Recent studies have shown that embedding similarity/dissimilarity measures between distributions in the variational level set framework can lead to effective object segmentation/t...
147
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CORR
2010
Springer
15 years 2 months ago
2010
Springer
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
118
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ICML
2004
IEEE
16 years 4 months ago
2004
IEEE
We consider the problem of decentralized detection under constraints on the number of bits that can be transmitted by each sensor. In contrast to most previous work, in which the ...
178
Voted
CORR
2011
Springer
14 years 7 months ago
2011
Springer
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...