Rahul Mazumder

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 79

Top Topics

Combinatorial Optimization

Media Streaming

Matrix Completion

Top Venues

J. Mach. Learn. Res.

Publications

Brian Liu, Rahul Mazumder
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests. CoRR (2024)
Xiang Meng, Kayhan Behdin, Haoyue Wang, Rahul Mazumder
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models. CoRR (2024)
Zirui Liu, Qingquan Song, Qiang Charles Xiao, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Xia Hu
FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference. CoRR (2024)
Shibal Ibrahim, Kayhan Behdin, Rahul Mazumder
End-to-end Feature Selection Approach for Learning Skinny Trees. AISTATS (2024)
Xiang Meng, Wenyu Chen, Riade Benbaki, Rahul Mazumder
FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning. AISTATS (2024)
Wenyu Chen, Rahul Mazumder
Subgradient Regularized Multivariate Convex Regression at Scale. SIAM J. Optim. 34 (3) (2024)
Brian Liu, Rahul Mazumder
FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML. KDD (2024)
Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization. CoRR (2024)
Wenyu Chen, Rahul Mazumder, Richard J. Samworth
A new computational framework for log-concave density estimation. Math. Program. Comput. 16 (2) (2024)
Brian Liu, Rahul Mazumder
FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML. CoRR (2024)
Xiang Meng, Wenyu Chen, Riade Benbaki, Rahul Mazumder
FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning. CoRR (2024)
Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. KDD (2023)
Kayhan Behdin, Qingquan Song, Aman Gupta, Ayan Acharya, David Durfee, Borja Ocejo, S. Sathiya Keerthi, Rahul Mazumder
mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization. CoRR (2023)
Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. CoRR (2023)
Brian Liu, Rahul Mazumder
ForestPrune: Compact Depth-Pruned Tree Ensembles. AISTATS (2023)
Hussein Hazimeh, Rahul Mazumder, Tim Nonet
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization. J. Mach. Learn. Res. 24 (2023)
Brian Liu, Rahul Mazumder
FIRE: An Optimization Approach for Fast Interpretable Rule Extraction. CoRR (2023)
Rahul Mazumder, Haoyue Wang
On the Convergence of CART under Sufficient Impurity Decrease Condition. CoRR (2023)
Wenyu Chen, Riade Benbaki, Yada Zhu, Rahul Mazumder
Dynamic Covariance Estimation under Structural Assumptions via a Joint Optimization Approach. ICAIF (2023)
Shibal Ibrahim, Gabriel Afriat, Kayhan Behdin, Rahul Mazumder
GRAND-SLAMIN' Interpretable Additive Modeling with Structural Constraints. NeurIPS (2023)
Kayhan Behdin, Wenyu Chen, Rahul Mazumder
Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives. CoRR (2023)
Shibal Ibrahim, Max Tell, Rahul Mazumder
Dyn-GWN: Time-Series Forecasting using Time-varying Graphs with Applications to Finance and Traffic Prediction. ICAIF (2023)
Rahul Mazumder, Peter Radchenko, Antoine Dedieu
Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low. Oper. Res. 71 (1) (2023)
Kayhan Behdin, Ayan Acharya, Aman Gupta, Sathiya Keerthi Selvaraj, Rahul Mazumder
QuantEase: Optimization-based Quantization for Language Models - An Efficient and Intuitive Algorithm. CoRR (2023)
Hanbyul Lee, Rahul Mazumder, Qifan Song, Jean Honorio
Matrix Completion from General Deterministic Sampling Patterns. CoRR (2023)
Brian Liu, Rahul Mazumder
Fire: An Optimization Approach for Fast Interpretable Rule Extraction. KDD (2023)
Aman Gupta, S. Sathiya Keerthi, Ayan Acharya, Miao Cheng, Borja Ocejo Elizondo, Rohan Ramanath, Rahul Mazumder, Kinjal Basu, J. Kenneth Tay, Rupesh Gupta
Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference. KDD (2023)
Ayan Acharya, Siyuan Gao, Borja Ocejo, Kinjal Basu, Ankan Saha, Sathiya Keerthi Selvaraj, Rahul Mazumder, Parag Agrawal, Aman Gupta
Promoting Inactive Members in Edge-Building Marketplace. WWW (Companion Volume) (2023)
Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. ICML (2023)
Shibal Ibrahim, Kayhan Behdin, Rahul Mazumder
End-to-end Feature Selection Approach for Learning Skinny Trees. CoRR (2023)
Rahul Mazumder, Haoyue Wang
On the Convergence of CART under Sufficient Impurity Decrease Condition. NeurIPS (2023)
Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. CoRR (2023)
Kayhan Behdin, Rahul Mazumder
Sharpness-Aware Minimization: An Implicit Regularization Perspective. CoRR (2023)
Rahul Mazumder, Haoyue Wang
Linear regression with partially mismatched data: local search with theoretical guarantees. Math. Program. 197 (2) (2023)
Ayan Acharya, Siyuan Gao, Ankan Saha, Borja Ocejo, Kinjal Basu, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Parag Agrawal
Optimizing for Member Value in an Edge Building Marketplace. CIKM (2023)
Kayhan Behdin, Qingquan Song, Aman Gupta, David Durfee, Ayan Acharya, S. Sathiya Keerthi, Rahul Mazumder
Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization. CoRR (2022)
Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu
Pushing the limits of fairness impossibility: Who's the fairest of them all? CoRR (2022)
Hussein Hazimeh, Rahul Mazumder, Tim Nonet
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization. CoRR (2022)
Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu
Pushing the limits of fairness impossibility: Who's the fairest of them all? NeurIPS (2022)
Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder
Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles. KDD (2022)
Brian Liu, Rahul Mazumder
ForestPrune: Compact Depth-Controlled Tree Ensembles. CoRR (2022)
Hussein Hazimeh, Rahul Mazumder, Ali Saab
Sparse regression at scale: branch-and-bound rooted in first-order optimization. Math. Program. 196 (1) (2022)
Haoyue Wang, Haihao Lu, Rahul Mazumder
Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning. SIAM J. Optim. 32 (4) (2022)
Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder
Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles. CoRR (2022)
Rahul Mazumder, Xiang Meng, Haoyue Wang
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features. ICML (2022)
Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder
Newer is Not Always Better: Rethinking Transferability Metrics, Their Peculiarities, Stability and Performance. ECML/PKDD (1) (2022)
Antoine Dedieu, Rahul Mazumder, Haoyue Wang
Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation. J. Mach. Learn. Res. 23 (2022)
Shibal Ibrahim, Wenyu Chen, Yada Zhu, Pin-Yu Chen, Yang Zhang, Rahul Mazumder
Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series. ICAIF (2022)
Rahul Mazumder, Xiang Meng, Haoyue Wang
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features. CoRR (2022)
Santanu S. Dey, Rahul Mazumder, Guanyi Wang
Using ℓ1-Relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA. Oper. Res. 70 (3) (2022)
Kayhan Behdin, Rahul Mazumder
Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification. CoRR (2021)
Hussein Hazimeh, Rahul Mazumder, Peter Radchenko
Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives. CoRR (2021)
Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. CoRR (2021)
Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder
Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance. CoRR (2021)
Rahul Mazumder, Haoyue Wang
Linear Regression with Mismatched Data: A Provably Optimal Local Search Algorithm. IPCO (2021)
Antoine Dedieu, Hussein Hazimeh, Rahul Mazumder
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives. J. Mach. Learn. Res. 22 (2021)
Gabriel Loewinger, Rolando Acosta Nunez, Rahul Mazumder, Giovanni Parmigiani
Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation. CoRR (2021)
Shibal Ibrahim, Rahul Mazumder, Peter Radchenko, Emanuel Ben-David
Predicting Census Survey Response Rates via Interpretable Nonparametric Additive Models with Structured Interactions. CoRR (2021)
Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. NeurIPS (2021)
Hussein Hazimeh, Rahul Mazumder
Learning Hierarchical Interactions at Scale: A Convex Optimization Approach. AISTATS (2020)
Antoine Dedieu, Hussein Hazimeh, Rahul Mazumder
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives. CoRR (2020)
Haihao Lu, Rahul Mazumder
Randomized Gradient Boosting Machine. SIAM J. Optim. 30 (4) (2020)
Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
The Tree Ensemble Layer: Differentiability meets Conditional Computation. ICML (2020)
Rahul Mazumder, Diego Saldana, Haolei Weng
Matrix completion with nonconvex regularization: spectral operators and scalable algorithms. Stat. Comput. 30 (4) (2020)
Kinjal Basu, Amol Ghoting, Rahul Mazumder, Yao Pan
ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications. ICML (2020)
Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
The Tree Ensemble Layer: Differentiability meets Conditional Computation. CoRR (2020)
Hussein Hazimeh, Rahul Mazumder
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms. Oper. Res. 68 (5) (2020)
Hussein Hazimeh, Rahul Mazumder, Ali Saab
Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization. CoRR (2020)
Koulik Khamaru, Rahul Mazumder
Computation of the maximum likelihood estimator in low-rank factor analysis. Math. Program. 176 (1-2) (2019)
Hari Bandi, Dimitris Bertsimas, Rahul Mazumder
Learning a Mixture of Gaussians via Mixed-Integer Optimization. INFORMS J. Optim. 1 (3) (2019)
Antoine Dedieu, Rahul Mazumder
Solving large-scale L1-regularized SVMs and cousins: the surprising effectiveness of column and constraint generation. CoRR (2019)
Hussein Hazimeh, Rahul Mazumder
Learning Hierarchical Interactions at Scale: A Convex Optimization Approach. CoRR (2019)
Antoine Dedieu, Rahul Mazumder, Zhen Zhu, Hossein Vahabi
Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming. CIKM (2018)
Antoine Dedieu, Rahul Mazumder, Zhen Zhu, Hossein Vahabi
Hierarchical Modeling and Shrinkage for User Session Length Prediction in Media Streaming. CoRR (2018)
Robert M. Freund, Paul Grigas, Rahul Mazumder
Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods. CoRR (2018)
Haihao Lu, Rahul Mazumder
Randomized Gradient Boosting Machine. CoRR (2018)
Robert M. Freund, Paul Grigas, Rahul Mazumder
An Extended Frank-Wolfe Method with "In-Face" Directions, and Its Application to Low-Rank Matrix Completion. SIAM J. Optim. 27 (1) (2017)
Rahul Mazumder, Peter Radchenko
The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization. IEEE Trans. Inf. Theory 63 (5) (2017)
Dimitris Bertsimas, Martin S. Copenhaver, Rahul Mazumder
Certifiably Optimal Low Rank Factor Analysis. J. Mach. Learn. Res. 18 (2017)
Trevor Hastie, Rahul Mazumder, Jason D. Lee, Reza Zadeh
Matrix completion and low-rank SVD via fast alternating least squares. J. Mach. Learn. Res. 16 (2015)
Robert M. Freund, Paul Grigas, Rahul Mazumder
A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives. CoRR (2015)
Dennis L. Sun, Rahul Mazumder
Non-negative matrix completion for bandwidth extension: A convex optimization approach. MLSP (2013)
Robert M. Freund, Paul Grigas, Rahul Mazumder
AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods. CoRR (2013)
Rahul Mazumder, Trevor Hastie
Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso. J. Mach. Learn. Res. 13 (2012)
Rahul Mazumder, Trevor Hastie
The Graphical Lasso: New Insights and Alternatives CoRR (2011)
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
Spectral Regularization Algorithms for Learning Large Incomplete Matrices. J. Mach. Learn. Res. 11 (2010)