A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation - researchr publication related

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Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep D. Ravikumar, Arindam Banerjee. A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation. In Peter L. Bartlett, Fernando C. N. Pereira, Christopher J. C. Burges, Léon Bottou, Kilian Q. Weinberger, editors, Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. pages 2339-2347, 2012. [doi]

The following publications are possibly variants of this publication:

QUIC: quadratic approximation for sparse inverse covariance estimationCho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep D. Ravikumar. jmlr, 15(1):2911-2947, 2014. [doi]

High-dimensional Sparse Inverse Covariance Estimation using Greedy MethodsChristopher C. Johnson, Ali Jalali, Pradeep D. Ravikumar. jmlr, 22:574-582, 2012. [doi]

BIG & QUIC: Sparse Inverse Covariance Estimation for a Million VariablesCho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep D. Ravikumar, Russell A. Poldrack. nips 2013: 3165-3173 [doi]

Sparse Inverse Covariance Matrix Estimation Using Quadratic ApproximationCho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep D. Ravikumar. nips 2011: 2330-2338 [doi]

Sparse inverse covariance matrix estimation using quadratic approximationInderjit S. Dhillon, Cho-Jui Hsieh, Mátyás A. Sustik, Pradeep D. Ravikumar. mlslp 2012: [doi]

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