Rahul Mazumder

25 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0003-1384-9743

MIT

Publications

• Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives — Operations Research 2026
• Multi-task learning for sparsity pattern heterogeneity: statistical and computational perspectives — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2026 (name-matched, not ORCID-linked)
• Predicting census survey response rates with parsimonious additive models and structured interactions — The Annals of Applied Statistics 2025 (name-matched, not ORCID-linked)
• Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Sparse NMF with Archetypal Regularization: Computational and Robustness Properties — Journal of Machine Learning Research 2024 (name-matched, not ORCID-linked)
• Grouped variable selection with discrete optimization: Computational and statistical perspectives — The Annals of Statistics 2023 (name-matched, not ORCID-linked)
• L0Learn: A Scalable Package for Sparse Learning using L0 Regularization — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low — Operations Research 2023
• Usingℓ1ℓ1-Relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA — Operations Research 2022
• Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
• Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms — Operations Research 2020
• Mining events with declassified diplomatic documents — The Annals of Applied Statistics 2020 (name-matched, not ORCID-linked)
• A Computational Framework for Multivariate Convex Regression and Its Variants — Journal of the American Statistical Association 2019 (name-matched, not ORCID-linked)
• Certifiably Optimal Low Rank Factor Analysis — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• A new perspective on boosting in linear regression via subgradient optimization and relatives — The Annals of Statistics 2017 (name-matched, not ORCID-linked)
• Best subset selection via a modern optimization lens — The Annals of Statistics 2016 (name-matched, not ORCID-linked)
• Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares — Journal of Machine Learning Research 2015 (name-matched, not ORCID-linked)
• Least quantile regression via modern optimization — The Annals of Statistics 2014 (name-matched, not ORCID-linked)
• Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso — Journal of Machine Learning Research 2012 (name-matched, not ORCID-linked)
• SparseNet: Coordinate Descent With Nonconvex Penalties — Journal of the American Statistical Association 2011 (name-matched, not ORCID-linked)
• Modeling item–item similarities for personalized recommendations on Yahoo! front page — The Annals of Applied Statistics 2011 (name-matched, not ORCID-linked)
• Spectral Regularization Algorithms for Learning Large Incomplete Matrices — Journal of Machine Learning Research 2010 (name-matched, not ORCID-linked)
• Modelling with categorical features via exact fusion and sparsity regularization — Journal of the Royal Statistical Society: Series B (Statistical Methodology) (name-matched, not ORCID-linked)
• Extracting Interpretable Models from Tree Ensembles: Computational and Statistical Perspectives — Journal of the American Statistical Association (name-matched, not ORCID-linked)