Rahul Mazumder

According to our database, Rahul Mazumder authored at least 70 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A new computational framework for log-concave density estimation.

Wenyu Chen, Rahul Mazumder, Richard J. Samworth

Math. Program. Comput., June, 2024

PolyCD: Optimization via Cycling through the Vertices of a Polytope.

Rahul Mazumder, Haoyue Wang

SIAM J. Optim., 2024

Subgradient Regularized Multivariate Convex Regression at Scale.

Wenyu Chen, Rahul Mazumder

SIAM J. Optim., 2024

Sparse NMF with Archetypal Regularization: Computational and Robustness Properties.

Kayhan Behdin, Rahul Mazumder

J. Mach. Learn. Res., 2024

ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models.

Xiang Meng, Kayhan Behdin, Haoyue Wang, Rahul Mazumder

CoRR, 2024

Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests.

Brian Liu, Rahul Mazumder

CoRR, 2024

FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference.

Zirui Liu, Qingquan Song, Qiang Charles Xiao, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Xia Hu

CoRR, 2024

FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML.

Brian Liu, Rahul Mazumder

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization.

Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder

Proceedings of the Forty-first International Conference on Machine Learning, 2024

FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning.

Xiang Meng, Wenyu Chen, Riade Benbaki, Rahul Mazumder

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

End-to-end Feature Selection Approach for Learning Skinny Trees.

Shibal Ibrahim, Kayhan Behdin, Rahul Mazumder

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Linear regression with partially mismatched data: local search with theoretical guarantees.

Rahul Mazumder, Haoyue Wang

Math. Program., February, 2023

Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low.

Rahul Mazumder, Peter Radchenko, Antoine Dedieu

Oper. Res., January, 2023

L0Learn: A Scalable Package for Sparse Learning using L0 Regularization.

Hussein Hazimeh, Rahul Mazumder, Tim Nonet

J. Mach. Learn. Res., 2023

QuantEase: Optimization-based Quantization for Language Models - An Efficient and Intuitive Algorithm.

Kayhan Behdin, Ayan Acharya, Aman Gupta, Sathiya Keerthi Selvaraj, Rahul Mazumder

CoRR, 2023

Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives.

Kayhan Behdin, Wenyu Chen, Rahul Mazumder

CoRR, 2023

Matrix Completion from General Deterministic Sampling Patterns.

Hanbyul Lee, Rahul Mazumder, Qifan Song, Jean Honorio

CoRR, 2023

Sharpness-Aware Minimization: An Implicit Regularization Perspective.

Kayhan Behdin, Rahul Mazumder

CoRR, 2023

mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization.

Kayhan Behdin, Qingquan Song, Aman Gupta, Ayan Acharya, David Durfee, Borja Ocejo, S. Sathiya Keerthi, Rahul Mazumder

CoRR, 2023

Promoting Inactive Members in Edge-Building Marketplace.

Ayan Acharya, Siyuan Gao, Borja Ocejo, Kinjal Basu, Ankan Saha, Sathiya Keerthi Selvaraj, Rahul Mazumder, Parag Agrawal, Aman Gupta

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

On the Convergence of CART under Sufficient Impurity Decrease Condition.

Rahul Mazumder, Haoyue Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GRAND-SLAMIN' Interpretable Additive Modeling with Structural Constraints.

Shibal Ibrahim, Gabriel Afriat, Kayhan Behdin, Rahul Mazumder

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fire: An Optimization Approach for Fast Interpretable Rule Extraction.

Brian Liu, Rahul Mazumder

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search.

Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference.

Aman Gupta, S. Sathiya Keerthi, Ayan Acharya, Miao Cheng, Borja Ocejo Elizondo, Rohan Ramanath, Rahul Mazumder, Kinjal Basu, J. Kenneth Tay, Rupesh Gupta

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Fast as CHITA: Neural Network Pruning with Combinatorial Optimization.

Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder

Proceedings of the International Conference on Machine Learning, 2023

Dyn-GWN: Time-Series Forecasting using Time-varying Graphs with Applications to Finance and Traffic Prediction.

Shibal Ibrahim, Max Tell, Rahul Mazumder

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Dynamic Covariance Estimation under Structural Assumptions via a Joint Optimization Approach.

Wenyu Chen, Riade Benbaki, Yada Zhu, Rahul Mazumder

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Optimizing for Member Value in an Edge Building Marketplace.

Ayan Acharya, Siyuan Gao, Ankan Saha, Borja Ocejo, Kinjal Basu, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Parag Agrawal

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

ForestPrune: Compact Depth-Pruned Tree Ensembles.

Brian Liu, Rahul Mazumder

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning.

Haoyue Wang, Haihao Lu, Rahul Mazumder

SIAM J. Optim., December, 2022

Sparse regression at scale: branch-and-bound rooted in first-order optimization.

Hussein Hazimeh, Rahul Mazumder, Ali Saab

Math. Program., 2022

Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation.

Antoine Dedieu, Rahul Mazumder, Haoyue Wang

J. Mach. Learn. Res., 2022

Using ℓ1-Relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA.

Santanu S. Dey, Rahul Mazumder, Guanyi Wang

Oper. Res., 2022

Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization.

Kayhan Behdin, Qingquan Song, Aman Gupta, David Durfee, Ayan Acharya, S. Sathiya Keerthi, Rahul Mazumder

CoRR, 2022

ForestPrune: Compact Depth-Controlled Tree Ensembles.

Brian Liu, Rahul Mazumder

CoRR, 2022

Newer is Not Always Better: Rethinking Transferability Metrics, Their Peculiarities, Stability and Performance.

Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Pushing the limits of fairness impossibility: Who's the fairest of them all?

Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles.

Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features.

Rahul Mazumder, Xiang Meng, Haoyue Wang

Proceedings of the International Conference on Machine Learning, 2022

Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series.

Shibal Ibrahim, Wenyu Chen, Yada Zhu, Pin-Yu Chen, Yang Zhang, Rahul Mazumder

Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2021

Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives.

Antoine Dedieu, Hussein Hazimeh, Rahul Mazumder

J. Mach. Learn. Res., 2021

Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation.

Gabriel Loewinger, Rolando Acosta Nunez, Rahul Mazumder, Giovanni Parmigiani

CoRR, 2021

Predicting Census Survey Response Rates via Interpretable Nonparametric Additive Models with Structured Interactions.

Shibal Ibrahim, Rahul Mazumder, Peter Radchenko, Emanuel Ben-David

CoRR, 2021

Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives.

Hussein Hazimeh, Rahul Mazumder, Peter Radchenko

CoRR, 2021

Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification.

Kayhan Behdin, Rahul Mazumder

CoRR, 2021

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 Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Linear Regression with Mismatched Data: A Provably Optimal Local Search Algorithm.

Rahul Mazumder, Haoyue Wang

Proceedings of the Integer Programming and Combinatorial Optimization, 2021

2020

Randomized Gradient Boosting Machine.

Haihao Lu, Rahul Mazumder

SIAM J. Optim., 2020

Matrix completion with nonconvex regularization: spectral operators and scalable algorithms.

Rahul Mazumder, Diego Saldana, Haolei Weng

Stat. Comput., 2020

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

Hussein Hazimeh, Rahul Mazumder

Oper. Res., 2020

The Tree Ensemble Layer: Differentiability meets Conditional Computation.

Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder

Proceedings of the 37th International Conference on Machine Learning, 2020

ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications.

Kinjal Basu, Amol Ghoting, Rahul Mazumder, Yao Pan

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning Hierarchical Interactions at Scale: A Convex Optimization Approach.

Hussein Hazimeh, Rahul Mazumder

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Learning a Mixture of Gaussians via Mixed-Integer Optimization.

Hari Bandi, Dimitris Bertsimas, Rahul Mazumder

INFORMS J. Optim., July, 2019

Computation of the maximum likelihood estimator in low-rank factor analysis.

Koulik Khamaru, Rahul Mazumder

Math. Program., 2019

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

Antoine Dedieu, Rahul Mazumder

CoRR, 2019

2018

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

Robert M. Freund, Paul Grigas, Rahul Mazumder

CoRR, 2018

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

Antoine Dedieu, Rahul Mazumder, Zhen Zhu, Hossein Vahabi

CoRR, 2018

Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming.

Antoine Dedieu, Rahul Mazumder, Zhen Zhu, Hossein Vahabi

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

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

Rahul Mazumder, Peter Radchenko

IEEE Trans. Inf. Theory, 2017

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

Robert M. Freund, Paul Grigas, Rahul Mazumder

SIAM J. Optim., 2017

Certifiably Optimal Low Rank Factor Analysis.

Dimitris Bertsimas, Martin S. Copenhaver, Rahul Mazumder

J. Mach. Learn. Res., 2017

2015

Matrix completion and low-rank SVD via fast alternating least squares.

Trevor Hastie, Rahul Mazumder, Jason D. Lee, Reza Zadeh

J. Mach. Learn. Res., 2015

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

Robert M. Freund, Paul Grigas, Rahul Mazumder

CoRR, 2015

2013

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

Robert M. Freund, Paul Grigas, Rahul Mazumder

CoRR, 2013

Non-negative matrix completion for bandwidth extension: A convex optimization approach.

Dennis L. Sun, Rahul Mazumder

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

2012

Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso.

Rahul Mazumder, Trevor Hastie

J. Mach. Learn. Res., 2012

2011

The Graphical Lasso: New Insights and Alternatives

Rahul Mazumder, Trevor Hastie

CoRR, 2011

2010

Spectral Regularization Algorithms for Learning Large Incomplete Matrices.

Rahul Mazumder, Trevor Hastie, Robert Tibshirani

J. Mach. Learn. Res., 2010