Rahul Mazumder

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Trevor HastieProfessor of Statistics, Stanford UniversityVerifierad e-postadress på stanford.edu
Hussein HazimehGoogle Research - Massachusetts Institute of TechnologyVerifierad e-postadress på mit.edu
Dimitris BertsimasBoeing Professor of Operations Research, MITVerifierad e-postadress på mit.edu
Kayhan BehdinLinkedInVerifierad e-postadress på mit.edu
Wenyu ChenMassachusetts Institute of TechnologyVerifierad e-postadress på mit.edu
Robert TibshiraniProfessor of Biomedical Data Sciences, and of Statistics, Stanford UniversityVerifierad e-postadress på stanford.edu
Shibal IbrahimMassachusetts Institute of TechnologyVerifierad e-postadress på mit.edu
Jerome FriedmanVerifierad e-postadress på stanford.edu
Haoyue WangMassachusetts Institute of TechnologyVerifierad e-postadress på mit.edu
Paul GrigasAssociate Professor, UC BerkeleyVerifierad e-postadress på berkeley.edu
Peter RadchenkoUniversity of SydneyVerifierad e-postadress på sydney.edu.au
Antoine DedieuSenior Research Scientist at Google DeepMindVerifierad e-postadress på deepmind.com
Robert M. FreundMassachusetts Institute of TechnologyVerifierad e-postadress på mit.edu
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityVerifierad e-postadress på princeton.edu
Reza Bosagh ZadehStanford and MatroidVerifierad e-postadress på stanford.edu
Martin S. CopenhaverJohns Hopkins Hospital & Johns Hopkins UniversityVerifierad e-postadress på mgh.harvard.edu
Santanu S. DeyGeorgia Institute of TechnologyVerifierad e-postadress på isye.gatech.edu
Guanyi WangAssistant Professor, National University of SingaporeVerifierad e-postadress på nus.edu.sg
Will FithianAssistant Professor in Statistics, University of California BerkeleyVerifierad e-postadress på berkeley.edu
Haihao (Sean) LuAssistant Professor, MITVerifierad e-postadress på mit.edu

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Rahul Mazumder

Massachusetts Institute of Technology

Verifierad e-postadress på mit.edu - Startsida

Statistics Mathematical Programming Machine Learning


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
Spectral regularization algorithms for learning large incomplete matrices R Mazumder, T Hastie, R Tibshirani The Journal of Machine Learning Research 11, 2287-2322, 2010	1854	2010
Best subset selection via a modern optimization lens D Bertsimas, A King, R Mazumder Annals of Statistics 44 (2), 813-852, 2016	1031	2016
Matrix completion and low-rank SVD via fast alternating least squares T Hastie, R Mazumder, JD Lee, R Zadeh The Journal of Machine Learning Research 16 (1), 3367-3402, 2015	672	2015
SparseNet: Coordinate Descent With Nonconvex Penalties R Mazumder, JH Friedman, T Hastie Journal of the American Statistical Association 106 (495), 1125-1138, 2011	585	2011
The graphical lasso: New insights and alternatives R Mazumder, T Hastie Electronic journal of statistics 6, 2125, 2012	393	2012
Exact covariance thresholding into connected components for large-scale graphical lasso R Mazumder, T Hastie The Journal of Machine Learning Research 13 (1), 781-794, 2012	276	2012
Fast best subset selection: Coordinate descent and local combinatorial optimization algorithms H Hazimeh, R Mazumder Operations Research 68 (5), 1517-1537, 2020	220	2020
Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning H Hazimeh, Z Zhao, A Chowdhery, M Sathiamoorthy, Y Chen, ... Advances in Neural Information Processing Systems 34, 29335-29347, 2021	141	2021
An extended Frank--Wolfe method with “in-face” directions, and its application to low-rank matrix completion RM Freund, P Grigas, R Mazumder SIAM Journal on optimization 27 (1), 319-346, 2017	141	2017
The tree ensemble layer: Differentiability meets conditional computation H Hazimeh, N Ponomareva, P Mol, Z Tan, R Mazumder International Conference on Machine Learning, 4138-4148, 2020	114	2020
A computational framework for multivariate convex regression and its variants R Mazumder, A Choudhury, G Iyengar, B Sen Journal of the American Statistical Association 114 (525), 318-331, 2019	114	2019
Subset selection with shrinkage: Sparse linear modeling when the SNR is low R Mazumder, P Radchenko, A Dedieu Operations Research 71 (1), 129-147, 2023	109	2023
Sparse regression at scale: branch-and-bound rooted in first-order optimization H Hazimeh, R Mazumder, A Saab Mathematical Programming, 2021	107	2021
A new perspective on boosting in linear regression via subgradient optimization and relatives R M. Freund, P Grigas, R Mazumder Annals of Statistics 45 (6), 2328-2364, 2017	78*	2017
Least quantile regression via modern optimization D Bertsimas, R Mazumder Annals of Statistics 42 (6), 2494-2525, 2014	74	2014
Certifiably optimal low rank factor analysis D Bertsimas, MS Copenhaver, R Mazumder Journal of Machine Learning Research 18 (29), 1-53, 2017	67	2017
Learning sparse classifiers: Continuous and mixed integer optimization perspectives A Dedieu, H Hazimeh, R Mazumder Journal of Machine Learning Research 22 (135), 1-47, 2021	59	2021
The trimmed lasso: Sparsity and robustness D Bertsimas, MS Copenhaver, R Mazumder arXiv preprint arXiv:1708.04527, 2017	53	2017
The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization R Mazumder, P Radchenko IEEE Transactions on Information Theory 63 (5), 3053-3075, 2017	52	2017
Using -Relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA SS Dey, R Mazumder, G Wang Operations Research 70 (3), 1914-1932, 2022	48*	2022

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