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Multivariate Convex Regression at Scale

May 23, 2020
Wenyu Chen, Rahul Mazumder


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Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization

Apr 13, 2020
Hussein Hazimeh, Rahul Mazumder, Ali Saab


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The Tree Ensemble Layer: Differentiability meets Conditional Computation

Feb 18, 2020
Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder


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Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives

Jan 17, 2020
Antoine Dedieu, Hussein Hazimeh, Rahul Mazumder


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Computing Estimators of Dantzig Selector type via Column and Constraint Generation

Aug 18, 2019
Rahul Mazumder, Stephen Wright, Andrew Zheng


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Learning Hierarchical Interactions at Scale: A Convex Optimization Approach

Feb 06, 2019
Hussein Hazimeh, Rahul Mazumder


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Solving large-scale L1-regularized SVMs and cousins: the surprising effectiveness of column and constraint generation

Jan 06, 2019
Antoine Dedieu, Rahul Mazumder


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Randomized Gradient Boosting Machine

Oct 28, 2018
Haihao Lu, Rahul Mazumder


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Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods

Oct 20, 2018
Robert M. Freund, Paul Grigas, Rahul Mazumder

* 38 pages 

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Hierarchical Modeling and Shrinkage for User Session Length Prediction in Media Streaming

Jun 22, 2018
Antoine Dedieu, Rahul Mazumder, Zhen Zhu, Hossein Vahabi

* 20 pages 

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Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms

Mar 06, 2018
Hussein Hazimeh, Rahul Mazumder


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Matrix Completion with Nonconvex Regularization: Spectral Operators and Scalable Algorithms

Jan 24, 2018
Rahul Mazumder, Diego F. Saldana, Haolei Weng


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Computation of the Maximum Likelihood estimator in low-rank Factor Analysis

Jan 18, 2018
Koulik Khamaru, Rahul Mazumder

* 22 pages, 4 figures 

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Flexible Low-Rank Statistical Modeling with Side Information

Aug 22, 2017
William Fithian, Rahul Mazumder

* 20 pages, 4 figures 

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The Trimmed Lasso: Sparsity and Robustness

Aug 15, 2017
Dimitris Bertsimas, Martin S. Copenhaver, Rahul Mazumder

* 32 pages (excluding appendix); 4 figures 

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Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is low

Aug 10, 2017
Rahul Mazumder, Peter Radchenko, Antoine Dedieu


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The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization

Jan 19, 2017
Rahul Mazumder, Peter Radchenko


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An Extended Frank-Wolfe Method with "In-Face" Directions, and its Application to Low-Rank Matrix Completion

Nov 06, 2015
Robert M. Freund, Paul Grigas, Rahul Mazumder

* 25 pages, 3 tables and 2 figues 

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Best Subset Selection via a Modern Optimization Lens

Jul 11, 2015
Dimitris Bertsimas, Angela King, Rahul Mazumder

* This is a revised version (May, 2015) of the first submission in June 2014 

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A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives

May 16, 2015
Robert M. Freund, Paul Grigas, Rahul Mazumder


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Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares

Oct 09, 2014
Trevor Hastie, Rahul Mazumder, Jason Lee, Reza Zadeh


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AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods

Jul 04, 2013
Robert M. Freund, Paul Grigas, Rahul Mazumder


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The Graphical Lasso: New Insights and Alternatives

Aug 07, 2012
Rahul Mazumder, Trevor Hastie

* This is a revised version of our previous manuscript with the same name ArXiv id: http://arxiv.org/abs/1111.5479 

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A Flexible, Scalable and Efficient Algorithmic Framework for Primal Graphical Lasso

Oct 25, 2011
Rahul Mazumder, Deepak K. Agarwal


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Exact covariance thresholding into connected components for large-scale Graphical Lasso

Sep 15, 2011
Rahul Mazumder, Trevor Hastie

* Report Version 2 (adding more experiments and correcting minor typos) 

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Regularization methods for learning incomplete matrices

Jun 11, 2009
Rahul Mazumder, Trevor Hastie, Rob Tibshirani

* 10 pages, 1 figure 

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