Log-Determinant Relaxation for Approximate. Inference in Discrete Markov Random Fields. Martin J. Wainwright and Michael I. Jordan, Fellow, IEEE. Abstract ...
This paper proposes a novel method, applicable to discrete-valued Markov random fields (MRFs) on arbitrary graphs, for approximately solving this ...
Jun 23, 2005 · Log-determinant relaxation for approximate inference in discrete Markov random fields. Martin J. Wainwright∗ and Michael I. Jordan†. Abstract.
A novel method, applicable to discrete-valued Markov random fields on arbitrary graphs, for approximately solving this marginalization problem, ...
Log-Determinant Relaxation for Approximate. Inference in Discrete Markov Random Fields. Martin J. Wainwright and Michael I. Jordan, Fellow, IEEE. Abstract ...
Mar 23, 2015 · This paper proposes a novel method, applicable to discrete-valued Markov random fields (MRFs) on arbitrary graphs, for approximately solving ...
May 31, 2019 · Wainwright M.J., Jordan M.I. Log-determinant relaxation for approximate inference in discrete Markov random fields. IEEE Trans. Signal ...
Log-determinant relaxation for approximate inference in discrete Markov random fields. ... Approximate inference algorithms for two-layer Bayesian networks.
[PDF] Semidefinite relaxations for approximate inference on graphs ...
cba.mit.edu › Wainwright.2.pdf
This paper introduces a new class of upper bounds based on solving a log-determinant maximization problem. Our derivation relies on a Gaussian upper bound on ...
Feb 21, 2018 · Log- determinant relaxation for approximate inference in dis- crete markov random fields. IEEE transactions on signal processing, 54(6):2099 ...