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Projected Subgradient Methods for Learning Sparse Gaussians

Duchi, John; Gould, Stephen; Koller, Daphne


Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our approach uses the ℓ1-norm as a regularization on the inverse covariance mat

CollectionsANU Research Publications
Date published: 2008
Type: Conference paper
Source: Proceedings of the Twenty Fourth Conference on Uncertainty in Artificial Intelligence


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