Perturb-and-MAP Random Fields: Using Discrete Optimization to Learn and Sample from Energy Models George Papandreou1 and Alan L. Yuille1,2 Department of Statistics, University of California, Los Angeles 2 Department of B

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Date: 2011-11-01 22:20:35 Statistical inference Probability theory Bayesian statistics Markov random field Maximum likelihood Gumbel distribution Expectation–maximization algorithm Perturbation theory Kullback–Leibler divergence Statistics Estimation theory Statistical theory		Perturb-and-MAP Random Fields: Using Discrete Optimization to Learn and Sample from Energy Models George Papandreou1 and Alan L. Yuille1,2 Department of Statistics, University of California, Los Angeles 2 Department of B Add to Reading List Source URL: www.stat.ucla.edu Download Document from Source Website File Size: 507,37 KB Share Document on Facebook

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