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144
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ALT
2007
Springer
16 years 1 months ago
2007
Springer
We consider the problem of learning and verifying hidden graphs and their properties given query access to the graphs. We analyze various queries (edge detection, edge counting, sh...
148
Voted
ALT
2003
Springer
16 years 1 months ago
2003
Springer
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
124
Voted
ICCAD
2006
IEEE
16 years 1 months ago
2006
IEEE
Reliable prediction of parametric yield for a specific design is difficult; a significant reason is the reliance of the yield estimation methods on the hard-to-measure distributio...
149
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CVPR
2010
IEEE
16 years 14 days ago
2010
IEEE
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
143
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CVPR
2010
IEEE
16 years 11 days ago
2010
IEEE
We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...