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Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS)

Oct 02, 2016
Hamed Firouzi, Alfred Hero, Bala Rajaratnam

* To appear in IEEE Transactions on Information Theory. 40 Pages. arXiv admin note: text overlap with arXiv:1303.2378 

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Foundational principles for large scale inference: Illustrations through correlation mining

May 18, 2015
Alfred O. Hero, Bala Rajaratnam

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Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection

Sep 12, 2014
Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam

* NIPS accepted version 

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A convex pseudo-likelihood framework for high dimensional partial correlation estimation with convergence guarantees

Aug 14, 2014
Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam

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G-AMA: Sparse Gaussian graphical model estimation via alternating minimization

May 14, 2014
Onkar Dalal, Bala Rajaratnam

* 21 pages, 3 figures 

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Duality in Graphical Models

Oct 09, 2013
Dhafer Malouche, Bala Rajaratnam, Benjamin T. Rolfs

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Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension

Apr 10, 2013
Hamed Firouzi, Bala Rajaratnam, Alfred Hero

* 31 pages, 9 figures, Appearing in Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS) 

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Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation

Nov 27, 2012
Dominique Guillot, Bala Rajaratnam, Benjamin T. Rolfs, Arian Maleki, Ian Wong

* 25 pages, 1 figure, 4 tables. Conference paper 

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A note on the lack of symmetry in the graphical lasso

Jul 23, 2012
Benjamin T. Rolfs, Bala Rajaratnam

* 9 pages, 2 figures 

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Large Scale Correlation Screening

Jun 26, 2011
Alfred O. Hero, Bala Rajaratnam

* 33 pages, 7 figures; Changes in version 2: There are no changes in the technical material in this revised version. The only changes are correcting typographical errors and referencing related work in the area. There is also material in the introduction where more context to the correlation screening problem is given (especially in terms of relationships to other testing methods) 

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