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Constrained Approximate Maximum Entropy Learning of Markov Random Fields
Varun Ganapathi
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Oznake: computer science;artificial intelligence
Parameter estimation in Markov random fields (MRFs) is a difficult task, in which inference over the network is run in the inner loop of a gradient descent procedure. Replacing exact inference with approximate methods such as loopy belief propagation (LBP) can suffer from poor convergence. In this p ...
Leto: 2008 Vir: videolectures.net
Poster Spotlights
Juan Carlos Niebles , Gerard Pons-Moll , Henning Hamer , Jianjian Xiao , Cheng-Hao Kuo , Louis Kratz , Lin Liang , Omar Oreifej , Yasushi Makihara , Jakob Santner , Raffay Hamid , Xuan Song , Hedvig Kjellstrom , Varun Ganapathi
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Oznake: computer science;computer vision;motion and tracking
Leto: 2010 Vir: videolectures.net
Št. zadetkov: 2
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