759 search results - page 9 / 152 » Structured Learning with Approximate Inference |
132
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ICML
2005
IEEE
16 years 5 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
135
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ICML
2004
IEEE
16 years 5 months ago
2004
IEEE
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
131
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EACL
2009
ACL Anthology
16 years 4 months ago
2009
ACL Anthology
We introduce cube summing, a technique that permits dynamic programming algorithms for summing over structures (like the forward and inside algorithms) to be extended with non-loc...
122
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AAAI
2008
15 years 6 months ago
2008
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
153
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JMLR
2010
14 years 11 months ago
2010
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...