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NIPS
2007

Cooled and Relaxed Survey Propagation for MRFs

9 years 1 months ago
Cooled and Relaxed Survey Propagation for MRFs
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.
Hai Leong Chieu, Wee Sun Lee, Yee Whye Teh
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where NIPS
Authors Hai Leong Chieu, Wee Sun Lee, Yee Whye Teh
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