Log-determinant relaxation for approximate inference in discrete Markov random fields

DOI10.1109/TSP.2006.874409zbMath1374.94616MaRDI QIDQ4588104

Martin J. Wainwright, Michael I. Jordan

Publication date: 30 October 2017

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (13)

Sampling Algorithms for Discrete Markov Random Fields and Related Graphical Models ⋮ Exploiting low-rank structure in semidefinite programming by approximate operator splitting ⋮ Superresolution with compound Markov random fields via the variational EM algorithm ⋮ Improved Variants of the Hutch++ Algorithm for Trace Estimation ⋮ On randomized trace estimates for indefinite matrices with an application to determinants ⋮ Fast Estimation of $tr(f(A))$ via Stochastic Lanczos Quadrature ⋮ Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations ⋮ Joint estimation of heterogeneous exponential Markov random fields through an approximate likelihood inference ⋮ A constrained \(\ell1\) minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models ⋮ Empirical comparison study of approximate methods for structure selection in binary graphical models ⋮ GRAPHICAL MODELS FOR CORRELATED DEFAULTS ⋮ Pursuit of food \textit{versus} pursuit of information in a Markovian perception-action loop model of foraging ⋮ Unnamed Item

This page was built for publication: Log-determinant relaxation for approximate inference in discrete Markov random fields