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|Title:||Cooled and relaxed survey propagation for MRFs||Authors:||Chieu, H.L.
|Issue Date:||2009||Citation:||Chieu, H.L.,Lee, W.S.,Teh, Y.-W. (2009). Cooled and relaxed survey propagation for MRFs. Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference. ScholarBank@NUS Repository.||Abstract:||We describe a new algorithm, Relaxed Survey Propagation (RSP), for finding MAP configurations in Markov random fields. We compare its performance with state-of-the-art algorithms including the max-product belief propagation, its sequential tree-reweighted variant, residual (sum-product) belief propagation, and tree-structured expectation propagation. We show that it outperforms all approaches for Ising models with mixed couplings, as well as on a web person disambiguation task formulated as a supervised clustering problem.||Source Title:||Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference||URI:||http://scholarbank.nus.edu.sg/handle/10635/41544||ISBN:||160560352X|
|Appears in Collections:||Staff Publications|
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