129 citations · 313 across the 10 of their papers we have counts for
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cs.LG2012★ 23 cited
Constrained Approximate Maximum Entropy Learning of Markov Random Fields
Varun Ganapathi, David Vickrey, John Duchi +1
Parameter estimation in Markov random fields (MRFs) is a difficult task, in which inference over the network is run in the inner loop of a gradient descent procedure. Replacing exa…
cs.LG2012★ 129 cited
Projected Subgradient Methods for Learning Sparse Gaussians
John Duchi, Stephen Gould, Daphne Koller
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 ap…