Fast Algorithms for Learning Latent Variables in Graphical Models

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Fast Algorithms for Learning Latent Variables in Graphical Models

27 June 2017

Mohammadreza Soltani

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Papers citing "Fast Algorithms for Learning Latent Variables in Graphical Models"

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Title
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach Dohyung Park Anastasios Kyrillidis Constantine Caramanis Sujay Sanghavi 67 180 0 12 Sep 2016
Dropping Convexity for Faster Semi-definite Optimization Srinadh Bhojanapalli Anastasios Kyrillidis Sujay Sanghavi 82 173 0 14 Sep 2015
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization Xiao-Tong Yuan Ping Li Tong Zhang 184 113 0 22 Nov 2013
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation Cho-Jui Hsieh Mátyás A. Sustik Inderjit S. Dhillon Pradeep Ravikumar 68 343 0 13 Jun 2013
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation D. Guillot B. Rajaratnam B. T. Rolfs A. Maleki Ian Wong 94 100 0 12 Nov 2012
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers S. Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu 477 1,379 0 13 Oct 2010
Latent variable graphical model selection via convex optimization V. Chandrasekaran P. Parrilo A. Willsky CML 209 509 0 06 Aug 2010
Guaranteed Rank Minimization via Singular Value Projection Raghu Meka Prateek Jain Inderjit S. Dhillon 191 554 0 30 Sep 2009
$High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence$ High-dimensional covariance estimation by minimizing $\ell_1$ -penalized log-determinant divergence Pradeep Ravikumar Martin J. Wainwright Garvesh Raskutti Bin Yu 251 873 0 21 Nov 2008
A randomized algorithm for principal component analysis V. Rokhlin Arthur Szlam M. Tygert 87 432 0 12 Sep 2008