Preprints/Papers Under Review

• Sparse PCA: A New Scalable Estimator Based On Integer Programming
  Kayhan Behdin and Rahul Mazumder (2021)
  ➥ Mixed Integer Programming Workshop student poster award (most popular poster), 2021
  - Code

• Predicting Census Survey Response Rates via Interpretable Nonparametric Additive Models with Structured Interactions
  Shibal Ibrahim, Rahul Mazumder, Peter Radchenko and Emanuel Ben-David (2021)
  - Code

• Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation
  Gabriel Loewinger, Rolando Acosta Nunez, Rahul Mazumder, Giovanni Parmigiani (2021)
  ➥ Best Abstract award at Annual Symposium Brigham Health/Harvard Medical School Computational Neuroscience Outcomes Center, 2020
  - Code

• Nonparametric Finite Mixture Models with Possible Shape Constraints: A Cubic Newton Approach
  Haoyue Wang, Rahul Mazumder and Shibal Ibrahim (2021)
  - Code

• A new computational framework for log-concave density estimation
  Wenyu Chen, Rahul Mazumder and Richard Samworth (2021)
  - Code

• Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification
  Kayhan Behdin and Rahul Mazumder (2021)
  - Code

• Multivariate Convex Regression at Scale
  Wenyu Chen and Rahul Mazumder (2020)
  - Code

• Computing Estimators of Dantzig Selector type via Column and Constraint Generation
  Rahul Mazumder, Stephen Wright and Andrew Zheng (2019)
  - Code

• Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods
  Robert Freund, Paul Grigas and Rahul Mazumder (2018)

• The Trimmed Lasso: Sparsity and Robustness
  Dimitris Bertsimas, Martin Copenhaver and Rahul Mazumder (2017)
  - Code

• Sparse principal component analysis and its L1-relaxation
  Santanu Dey, Rahul Mazumder, Marco Molinaro and Guanyi Wang (2017)

• Scalable Computation of Regularized Precision Matrices via Stochastic Optimization
  Yves F. Atchadé, Rahul Mazumder and Jie Chen (2015)

Published/To Appear Journal Articles

Methodology oriented Journal Articles

• Linear regression with partially mismatched data: local search with theoretical guarantees
  Haoyue Wang and Rahul Mazumder
  Mathematical Programming (forthcoming) (2022)
  - An extended abstract of this paper appeared in IPCO 2021

• Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning
  Haoyue Wang, Haihao Lu and Rahul Mazumder
  SIAM Journal on Optimization (forthcoming) (2022)
  - Code

• Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives
  Hussein Hazimeh, Rahul Mazumder and Peter Radchenko
  Annals of Statistics (forthcoming) (2022+)
  - Code

• Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is low
  Rahul Mazumder, Peter Radchenko and Antoine Dedieu
  Operations Research (to appear) (2021+)
  - Code

• Solving L1-regularized SVMs and related linear programs: Revisiting the effectiveness of Column and Constraint Generation
  Antoine Dedieu, Rahul Mazumder and Haoyue Wang
  Journal of Machine Learning Research (2022)
  - Code

• Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization
  Hussein Hazimeh, Rahul Mazumder and Ali Saab
  Mathematical Programming (2021)
  ➥ MIT Operations Research Center best student paper award, 2020
  ➥ INFORMS Computing Society best student paper award (honorable mention), 2020
  ➥ Mixed Integer Programming Workshop Student Poster Award (honorable mention), 2019
  - Code

• Using L1-relaxation and integer programming to obtain dual bounds for sparse PCA
  Santanu Dey, Rahul Mazumder and Guanyi Wang
  Operations Research (2021+) (to appear)

• Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives
  Antoine Dedieu, Hussein Hazimeh and Rahul Mazumder
  Journal of Machine Learning Research (2021)
  - Code on CRAN and Github

• Randomized Gradient Boosting Machine
  Haihao Lu and Rahul Mazumder
  SIAM Journal on Optimization (2020)
  - Code

• Computing the degrees of freedom of rank-regularized estimators and cousins
  Rahul Mazumder and Haolei Weng
  Electronic Journal of Statistics (2020)

• Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms
  Hussein Hazimeh and Rahul Mazumder
  Operations Research (2020)
  ➥ INFORMS Optimization Society Young Researchers Award 2020
  - Code on CRAN and Github

• Discussion of ``Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons"
  Rahul Mazumder
  Statistical Science (2020)

• Matrix Completion with Nonconvex Regularization: Spectral Operators and Scalable Algorithms
  Rahul Mazumder, Diego F. Saldana and Haolei Weng
  Statistics and Computing (2020)
  - Code

• Computation of the Maximum Likelihood estimator in low-rank Factor Analysis
  Koulik Khamaru and Rahul Mazumder
  Mathematical Programming (2019)
  - Code

• Learning a Mixture of Gaussians via Mixed Integer Optimization
  Hari Bandi, Dimitris Bertsimas and Rahul Mazumder
  INFORMS Journal on Optimization (2019)

• A Computational Framework for Multivariate Convex Regression and its Variants
  Rahul Mazumder, Arkopal Choudhury, Garud Iyengar and Bodhisattva Sen
  Journal of the American Statistical Association (2019)
  - Code

• Flexible Low-Rank Statistical Modeling with Missing Data and Side Information
  Will Fithian and Rahul Mazumder
  Statistical Science (2018)
  Previously circulated as: Scalable Convex Methods for Flexible Low-Rank Matrix Modeling

• Certifiably Optimal Low Rank Factor Analysis
  Dimitris Bertsimas, Martin Copenhaver and Rahul Mazumder
  Journal of Machine Learning Research (2017)
  - Code

• The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization
  Rahul Mazumder and Peter Radchenko
  IEEE Transactions on Information Theory (2017)

• An Extended Frank-Wolfe Method with "In-Face" Directions, and its Application to Low-Rank Matrix Completion
  Robert M. Freund, Paul Grigas and Rahul Mazumder
  SIAM Journal on Optimization (2017)
  - Code

• A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives
  Robert M. Freund, Paul Grigas and Rahul Mazumder
  Annals of Statistics (2017)
  ➥ Annals of Statistics, Special Invited Session at the Joint Statistical Meetings (JSM) 2017
  ➥ INFORMS Optimization Society student paper award 2015

• Best Subset Selection via a Modern Optimization Lens
  Dimitris Bertsimas, Angela King and Rahul Mazumder
  Annals of Statistics (2016)
  - Code (hosted on Gurobi's github repository)

• Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares
  Trevor Hastie, Rahul Mazumder, Jason Lee, Reza Zadeh
  Journal of Machine Learning Research (2015)
  - Code

• Least Quantile of Squares Regression via Modern Optimization
  Dimitris Bertsimas and Rahul Mazumder
  Annals of Statistics (2014)

• The Graphical Lasso: New Insights and Alternatives
  Rahul Mazumder and Trevor Hastie
  Electronic Journal of Statistics (2012)
  - Code

• Exact covariance thresholding into connected components for large-scale Graphical Lasso
  Rahul Mazumder and Trevor Hastie
  Journal of Machine Learning Research (2012)

• SparseNet: Coordinate Descent with Non-Convex Penalties
  Rahul Mazumder, Jerome Friedman and Trevor Hastie
  Journal of the American Statistical Association (2011)
  - Code

• Spectral Regularization Algorithms for Learning Large Incomplete Matrices
  Rahul Mazumder, Trevor Hastie and Rob Tibshirani
  Journal of Machine Learning Research (2010)
  - Code

Application-oriented Journal Articles

• Integration of Survival Data from Multiple Studies
  Steffen Ventz, Rahul Mazumder and Lorenzo Trippa
  Biometrics (2021)
  - Code

• Analysis of correlations between local geographic atrophy growth rates and local OCT angiography-measured choriocapillaris flow deficits
  Eric M Moult, Yingying Shi, Qinqin Zhang, Liang Wang, Rahul Mazumder, Siyu Chen, Zhongdi Chu, William Feuer, Nadia K Waheed, Giovanni Gregori, Ruikang K Wang, Philip J Rosenfeld, James G Fujimoto
  Biomedical Optics Express (2021)

• Mining Events with Declassified Diplomatic Documents
  Yuanjun Gao, Jack Goetz, Rahul Mazumder, Matthew Connelly
  Annals of Applied Statistics (2020)
  - Code (can be found in journal supplementary material)
  - Media Article

• Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach
  Julia Validomat, Rahul Mazumder, Alex McInturff, Douglas McCauley and Trevor Hastie
  Biometrics (2014)
  - Code (can be found in journal supplementary material)

• Turbulence, suspension and downstream fining due to flow over a sand-gravel mixture bed
  Koeli Ghoshal, Rahul Mazumder, Chandan Chakraborty and Bijoy. S. Mazumder
  International Journal of Sediment Research (2013)

• Modeling Item-Item Similarities for Personalized Recommendations on Yahoo! Front Page
  Deepak Agarwal, Liang Zhang and Rahul Mazumder
  Annals of Applied Statistics (2011)

• Fluid flow pattern analysis in a trough region: a nonparametric approach
  Rahul Mazumder
  Journal of Applied Statistics (2008)

• Clustering based on geometry and interactions of turbulence bursting rate processes in a trough region
  Rahul Mazumder
  Environmetrics (2007)

• Statistical characterization of circulation patterns and direction of turbulent flow over a waveform structure
  Rahul Mazumder and Bijoy S. Mazumder
  Environmetrics (2006)

Peer Reviewed Conference Articles

• Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles
  Shibal Ibrahim, Hussein Hazimeh, and Rahul Mazumder
  28th SIGKDD Conference on Knowledge Discovery and Data Mining, KDD (2022)

• Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features
  Rahul Mazumder, Xiang Meng, and Haoyue Wang
  Proceedings of the 39th International Conference on Machine Learning, ICML (2022)

• DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning
  Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi
  Proceedings of the 35th Conference on Neural Information Processing Systems, NeurIPS (2021)
  - Code (hosted on Google's Github repository)

• Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series
  Shibal Ibrahim, Wenyu Chen, Yada Zhu, Yang Zhang, Pin-yu Chen and Rahul Mazumder
  KDD 2021 Workshop on Machine Learning in Finance

• Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance
  Shibal Ibrahim, Natalia Ponomareva and Rahul Mazumder
  NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and Applications

• Linear Regression with Mismatched Data: a Provably Optimal Local Search Algorithm
  Haoyue Wang and Rahul Mazumder
  Proceedings of the 22nd International Conference on Integer Programming and Combinatorial Optimization, IPCO (2021)
  - A journal version of this extended abstract can be found here

• ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications
  Kinjal Basu, Amol Ghoting, Rahul Mazumder and Yao Pan
  Proceedings of the 37th International Conference on Machine Learning, ICML (2020)
  - Blog article by LinkedIn
  - Code (hosted on LinkedIn's github repository)

• The Tree Ensemble Layer: Differentiability meets Conditional Computation
  Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan and Rahul Mazumder
  Proceedings of the 37th International Conference on Machine Learning, ICML (2020)
  - Code (hosted on Google's github repository)

• Learning Hierarchical Interactions at Scale: A Convex Optimization Approach
  Hussein Hazimeh and Rahul Mazumder
  Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, AISTATS (2020)
  ➥ Mixed Integer Programming Workshop Student Poster Award (honorable mention), 2019
  - Code

• Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming
  Antoine Dedieu, Rahul Mazumder, Zhen Zhu and Hossein Vahabi
  Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM (2018)
  - Code

• Non-Negative Matrix Completion for Bandwidth Extension: A Convex Optimization Approach
  Dennis Sun and Rahul Mazumder
  IEEE Workshop on Machine Learning for Signal Processing, MLSP (2013)

• Projected likelihood contrasts for testing homogeneity in finite mixture models with nuisance parameters
  Debapriya Sengupta and Rahul Mazumder
  Beyond Parametrics in Interdisciplinary Research: Festschrift in Honor of Professor Pranab K. Sen. Institute of Mathematical Statistics (2008)

Theses

• Topics in Sparse Multivariate Statistics
  Ph.D. Thesis, Stanford University (Deptartment of Statistics), 2012.
  Advisor: Trevor Hastie. (Other committee members: Candes, Friedman, Tibshirani, Saunders).

• Local scale-space contrasts via Gaussian Mixture Ensembles for speech signal segmentation
  MStat Thesis, Indian Statistical Institute, 2007.
  Tata Consultancy Services (TCS) award for the best Masters thesis