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NIPS
2001

TAP Gibbs Free Energy, Belief Propagation and Sparsity

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TAP Gibbs Free Energy, Belief Propagation and Sparsity
The adaptive TAP Gibbs free energy for a general densely connected probabilistic model with quadratic interactions and arbritary single site constraints is derived. We show how a specific sequential minimization of the free energy leads to a generalization of Minka's expectation propagation. Lastly, we derive a sparse representation version of the sequential algorithm. The usefulness of the approach is demonstrated on classification and density estimation with Gaussian processes and on an independent component analysis problem.
Lehel Csató, Manfred Opper, Ole Winther
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where NIPS
Authors Lehel Csató, Manfred Opper, Ole Winther
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