Rahul Mazumder

112 papers A* 16A 6B 1Journal 78Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	3BASiL: An Algorithmic Framework for Sparse plus Low-Rank Compression of LLMs. CoRR Mehdi Makni, Xiang Meng, Rahul Mazumder
2026	J	`jnl`	DuaLip-GPU Technical Report. CoRR Gregory Dexter, Aida Rahmattalabi, Sanjana Garg, Qinquan Song, Ruby Tu, Yuan Gao, Yi Zhang, Zhipeng Wang, Rahul Mazumder
2026	J	`jnl`	Robust Batch-Level Query Routing for Large Language Models under Cost and Capacity Constraints. CoRR Jelena Markovic-Voronov, Kayhan Behdin, Yuanda Xu, Zhengze Zhou, Zhipeng Wang, Rahul Mazumder
2025	—	`conf`	A unified framework for Sparse plus Low-Rank Matrix Decomposition for LLMs. CPAL Mehdi Makni, Kayhan Behdin, Zheng Xu, Natalia Ponomareva, Rahul Mazumder
2025	J	`jnl`	An Optimization Framework for Differentially Private Sparse Fine-Tuning. CoRR Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Hussein Hazimeh, Rahul Mazumder
2025	J	`jnl`	Differentially Private High-dimensional Variable Selection via Integer Programming. CoRR Petros Prastakos, Kayhan Behdin, Rahul Mazumder
2025	J	`jnl`	Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications. CoRR Kayhan Behdin, Yun Dai, Ata Fatahi Baarzi, Aman Gupta, Qingquan Song, Shao Tang, Hejian Sang, Gregory Dexter, Sirou Zhu, Siyu Zhu, Tejas Dharamsi, Maziar Sanjabi, Vignesh Kothapalli, Hamed Firooz, Zhoutong Fu, Yihan Cao, Pin-Lun Hsu, Fedor Borisyuk, Zhipeng Wang, Rahul Mazumder, Natesh S. Pillai, Luke Simon
2025	—	`conf`	Efficient Algorithms for Leveraging LLMs for Generative and Predictive Recommender Systems. WWW (Companion Volume) Kayhan Behdin, Yun Dai, Gregory Dexter, Aman Gupta, Rahul Mazumder, Ankan Saha, Qingquan Song, Shao Tang, Sirou Zhu, Pin-Lun Hsu
2025	J	`jnl`	Extracting Interpretable Models from Tree Ensembles: Computational and Statistical Perspectives. CoRR Brian Liu, Rahul Mazumder, Peter Radchenko
2025	J	`jnl`	HASSLE-free: A unified Framework for Sparse plus Low-Rank Matrix Decomposition for LLMs. CoRR Mehdi Makni, Kayhan Behdin, Zheng Xu, Natalia Ponomareva, Rahul Mazumder
2025	—	`conf`	MOSS: Multi-Objective Optimization for Stable Rule Sets. KDD (2) Brian Liu, Rahul Mazumder
2025	J	`jnl`	MOSS: Multi-Objective Optimization for Stable Rule Sets. CoRR Brian Liu, Rahul Mazumder
2025	J	`jnl`	Nonparametric Finite Mixture Models with Possible Shape Constraints: A Cubic Newton Approach. SIAM J. Math. Data Sci. Haoyue Wang, Shibal Ibrahim, Rahul Mazumder
2025	A*	`conf`	Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework. ICLR Ryan Lucas, Rahul Mazumder
2025	J	`jnl`	Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests. J. Mach. Learn. Res. Brian Liu, Rahul Mazumder
2025	J	`jnl`	Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction. CoRR Ryan Lucas, Kayhan Behdin, Zhipeng Wang, Qingquan Song, Shao Tang, Rahul Mazumder
2025	—	`conf`	SPARTA: An Optimization Framework for Differentially Private Sparse Fine-Tuning. KDD (2) Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Rahul Mazumder, Hussein Hazimeh
2025	—	`conf`	Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems. EMNLP (Industry Track) Kayhan Behdin, Ata Fatahi Baarzi, Qingquan Song, Yun Dai, Aman Gupta, Zhipeng Wang, Hejian Sang, Shao Tang, Gregory Dexter, Sirou Zhu, Siyu Zhu, Tejas Dharamsi, Vignesh Kothapalli, Zhoutong Fu, Yihan Cao, Pin-Lun Hsu, Fedor Borisyuk, Natesh S. Pillai, Luke Simon, Rahul Mazumder
2025	J	`jnl`	TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks. CoRR Xiang Meng, Mehdi Makni, Rahul Mazumder
2025	J	`jnl`	Theoretical Compression Bounds for Wide Multilayer Perceptrons. CoRR Houssam El Cheairi, David Gamarnik, Rahul Mazumder
2024	J	`jnl`	A new computational framework for log-concave density estimation. Math. Program. Comput. Wenyu Chen, Rahul Mazumder, Richard J. Samworth
2024	A*	`conf`	ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models. NeurIPS Xiang Meng, Kayhan Behdin, Haoyue Wang, Rahul Mazumder
2024	J	`jnl`	ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models. CoRR Xiang Meng, Kayhan Behdin, Haoyue Wang, Rahul Mazumder
2024	J	`jnl`	Efficient user history modeling with amortized inference for deep learning recommendation models. CoRR Lars Hertel, Neil Daftary, Fedor Borisyuk, Aman Gupta, Rahul Mazumder
2024	A	`conf`	End-to-end Feature Selection Approach for Learning Skinny Trees. AISTATS Shibal Ibrahim, Kayhan Behdin, Rahul Mazumder
2024	A	`conf`	FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning. AISTATS Xiang Meng, Wenyu Chen, Riade Benbaki, Rahul Mazumder
2024	J	`jnl`	FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning. CoRR Xiang Meng, Wenyu Chen, Riade Benbaki, Rahul Mazumder
2024	A*	`conf`	FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML. KDD Brian Liu, Rahul Mazumder
2024	J	`jnl`	FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML. CoRR Brian Liu, Rahul Mazumder
2024	J	`jnl`	FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference. CoRR Zirui Liu, Qingquan Song, Qiang Charles Xiao, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Xia Hu
2024	A*	`conf`	OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization. ICML Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder
2024	J	`jnl`	OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization. CoRR Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder
2024	J	`jnl`	PolyCD: Optimization via Cycling through the Vertices of a Polytope. SIAM J. Optim. Rahul Mazumder, Haoyue Wang
2024	J	`jnl`	Preserving Deep Representations In One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework. CoRR Ryan Lucas, Rahul Mazumder
2024	J	`jnl`	Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests. CoRR Brian Liu, Rahul Mazumder
2024	J	`jnl`	Sparse NMF with Archetypal Regularization: Computational and Robustness Properties. J. Mach. Learn. Res. Kayhan Behdin, Rahul Mazumder
2024	J	`jnl`	Subgradient Regularized Multivariate Convex Regression at Scale. SIAM J. Optim. Wenyu Chen, Rahul Mazumder
2023	A*	`conf`	COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. KDD Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	J	`jnl`	COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. CoRR Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	—	`conf`	Dyn-GWN: Time-Series Forecasting using Time-varying Graphs with Applications to Finance and Traffic Prediction. ICAIF Shibal Ibrahim, Max Tell, Rahul Mazumder
2023	—	`conf`	Dynamic Covariance Estimation under Structural Assumptions via a Joint Optimization Approach. ICAIF Wenyu Chen, Riade Benbaki, Yada Zhu, Rahul Mazumder
2023	J	`jnl`	End-to-end Feature Selection Approach for Learning Skinny Trees. CoRR Shibal Ibrahim, Kayhan Behdin, Rahul Mazumder
2023	J	`jnl`	FIRE: An Optimization Approach for Fast Interpretable Rule Extraction. CoRR Brian Liu, Rahul Mazumder
2023	A*	`conf`	Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. ICML Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	J	`jnl`	Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. CoRR Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	A*	`conf`	Fire: An Optimization Approach for Fast Interpretable Rule Extraction. KDD Brian Liu, Rahul Mazumder
2023	A	`conf`	ForestPrune: Compact Depth-Pruned Tree Ensembles. AISTATS Brian Liu, Rahul Mazumder
2023	A*	`conf`	GRAND-SLAMIN' Interpretable Additive Modeling with Structural Constraints. NeurIPS Shibal Ibrahim, Gabriel Afriat, Kayhan Behdin, Rahul Mazumder
2023	J	`jnl`	L0Learn: A Scalable Package for Sparse Learning using L0 Regularization. J. Mach. Learn. Res. Hussein Hazimeh, Rahul Mazumder, Tim Nonet
2023	J	`jnl`	Linear regression with partially mismatched data: local search with theoretical guarantees. Math. Program. Rahul Mazumder, Haoyue Wang
2023	J	`jnl`	Matrix Completion from General Deterministic Sampling Patterns. CoRR Hanbyul Lee, Rahul Mazumder, Qifan Song, Jean Honorio
2023	A*	`conf`	On the Convergence of CART under Sufficient Impurity Decrease Condition. NeurIPS Rahul Mazumder, Haoyue Wang
2023	J	`jnl`	On the Convergence of CART under Sufficient Impurity Decrease Condition. CoRR Rahul Mazumder, Haoyue Wang
2023	A	`conf`	Optimizing for Member Value in an Edge Building Marketplace. CIKM Ayan Acharya, Siyuan Gao, Ankan Saha, Borja Ocejo, Kinjal Basu, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Parag Agrawal
2023	A*	`conf`	Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference. KDD Aman Gupta, S. Sathiya Keerthi, Ayan Acharya, Miao Cheng, Borja Ocejo Elizondo, Rohan Ramanath, Rahul Mazumder, Kinjal Basu, J. Kenneth Tay, Rupesh Gupta
2023	—	`conf`	Promoting Inactive Members in Edge-Building Marketplace. WWW (Companion Volume) Ayan Acharya, Siyuan Gao, Borja Ocejo, Kinjal Basu, Ankan Saha, Sathiya Keerthi Selvaraj, Rahul Mazumder, Parag Agrawal, Aman Gupta
2023	J	`jnl`	QuantEase: Optimization-based Quantization for Language Models - An Efficient and Intuitive Algorithm. CoRR Kayhan Behdin, Ayan Acharya, Aman Gupta, Sathiya Keerthi Selvaraj, Rahul Mazumder
2023	J	`jnl`	Sharpness-Aware Minimization: An Implicit Regularization Perspective. CoRR Kayhan Behdin, Rahul Mazumder
2023	J	`jnl`	Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives. CoRR Kayhan Behdin, Wenyu Chen, Rahul Mazumder
2023	J	`jnl`	Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low. Oper. Res. Rahul Mazumder, Peter Radchenko, Antoine Dedieu
2023	J	`jnl`	mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization. CoRR Kayhan Behdin, Qingquan Song, Aman Gupta, Ayan Acharya, David Durfee, Borja Ocejo, S. Sathiya Keerthi, Rahul Mazumder
2022	A*	`conf`	Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles. KDD Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder
2022	J	`jnl`	Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles. CoRR Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder
2022	J	`jnl`	ForestPrune: Compact Depth-Controlled Tree Ensembles. CoRR Brian Liu, Rahul Mazumder
2022	J	`jnl`	Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning. SIAM J. Optim. Haoyue Wang, Haihao Lu, Rahul Mazumder
2022	J	`jnl`	Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization. CoRR Kayhan Behdin, Qingquan Song, Aman Gupta, David Durfee, Ayan Acharya, S. Sathiya Keerthi, Rahul Mazumder
2022	—	`conf`	Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series. ICAIF Shibal Ibrahim, Wenyu Chen, Yada Zhu, Pin-Yu Chen, Yang Zhang, Rahul Mazumder
2022	J	`jnl`	L0Learn: A Scalable Package for Sparse Learning using L0 Regularization. CoRR Hussein Hazimeh, Rahul Mazumder, Tim Nonet
2022	—	`conf`	Newer is Not Always Better: Rethinking Transferability Metrics, Their Peculiarities, Stability and Performance. ECML/PKDD (1) Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder
2022	A*	`conf`	Pushing the limits of fairness impossibility: Who's the fairest of them all? NeurIPS Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu
2022	J	`jnl`	Pushing the limits of fairness impossibility: Who's the fairest of them all? CoRR Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu
2022	A*	`conf`	Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features. ICML Rahul Mazumder, Xiang Meng, Haoyue Wang
2022	J	`jnl`	Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features. CoRR Rahul Mazumder, Xiang Meng, Haoyue Wang
2022	J	`jnl`	Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation. J. Mach. Learn. Res. Antoine Dedieu, Rahul Mazumder, Haoyue Wang
2022	J	`jnl`	Sparse regression at scale: branch-and-bound rooted in first-order optimization. Math. Program. Hussein Hazimeh, Rahul Mazumder, Ali Saab
2022	J	`jnl`	Using ℓ1-Relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA. Oper. Res. Santanu S. Dey, Rahul Mazumder, Guanyi Wang
2021	J	`jnl`	Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification. CoRR Kayhan Behdin, Rahul Mazumder
2021	A*	`conf`	DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. NeurIPS Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi
2021	J	`jnl`	DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. CoRR Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi
2021	J	`jnl`	Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives. CoRR Hussein Hazimeh, Rahul Mazumder, Peter Radchenko
2021	J	`jnl`	Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives. J. Mach. Learn. Res. Antoine Dedieu, Hussein Hazimeh, Rahul Mazumder
2021	B	`conf`	Linear Regression with Mismatched Data: A Provably Optimal Local Search Algorithm. IPCO Rahul Mazumder, Haoyue Wang
2021	J	`jnl`	Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance. CoRR Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder
2021	J	`jnl`	Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation. CoRR Gabriel Loewinger, Rolando Acosta Nunez, Rahul Mazumder, Giovanni Parmigiani
2021	J	`jnl`	Predicting Census Survey Response Rates via Interpretable Nonparametric Additive Models with Structured Interactions. CoRR Shibal Ibrahim, Rahul Mazumder, Peter Radchenko, Emanuel Ben-David
2020	A*	`conf`	ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications. ICML Kinjal Basu, Amol Ghoting, Rahul Mazumder, Yao Pan
2020	J	`jnl`	Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms. Oper. Res. Hussein Hazimeh, Rahul Mazumder
2020	A	`conf`	Learning Hierarchical Interactions at Scale: A Convex Optimization Approach. AISTATS Hussein Hazimeh, Rahul Mazumder
2020	J	`jnl`	Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives. CoRR Antoine Dedieu, Hussein Hazimeh, Rahul Mazumder
2020	J	`jnl`	Matrix completion with nonconvex regularization: spectral operators and scalable algorithms. Stat. Comput. Rahul Mazumder, Diego Saldana, Haolei Weng
2020	J	`jnl`	Randomized Gradient Boosting Machine. SIAM J. Optim. Haihao Lu, Rahul Mazumder
2020	J	`jnl`	Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization. CoRR Hussein Hazimeh, Rahul Mazumder, Ali Saab
2020	A*	`conf`	The Tree Ensemble Layer: Differentiability meets Conditional Computation. ICML Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
2020	J	`jnl`	The Tree Ensemble Layer: Differentiability meets Conditional Computation. CoRR Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
2019	J	`jnl`	Computation of the maximum likelihood estimator in low-rank factor analysis. Math. Program. Koulik Khamaru, Rahul Mazumder
2019	J	`jnl`	Learning Hierarchical Interactions at Scale: A Convex Optimization Approach. CoRR Hussein Hazimeh, Rahul Mazumder
2019	J	`jnl`	Learning a Mixture of Gaussians via Mixed-Integer Optimization. INFORMS J. Optim. Hari Bandi, Dimitris Bertsimas, Rahul Mazumder
2019	J	`jnl`	Solving large-scale L1-regularized SVMs and cousins: the surprising effectiveness of column and constraint generation. CoRR Antoine Dedieu, Rahul Mazumder
2018	J	`jnl`	Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods. CoRR Robert M. Freund, Paul Grigas, Rahul Mazumder
2018	J	`jnl`	Hierarchical Modeling and Shrinkage for User Session Length Prediction in Media Streaming. CoRR Antoine Dedieu, Rahul Mazumder, Zhen Zhu, Hossein Vahabi
2018	A	`conf`	Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming. CIKM Antoine Dedieu, Rahul Mazumder, Zhen Zhu, Hossein Vahabi
2018	J	`jnl`	Randomized Gradient Boosting Machine. CoRR Haihao Lu, Rahul Mazumder
2017	J	`jnl`	An Extended Frank-Wolfe Method with "In-Face" Directions, and Its Application to Low-Rank Matrix Completion. SIAM J. Optim. Robert M. Freund, Paul Grigas, Rahul Mazumder
2017	J	`jnl`	Certifiably Optimal Low Rank Factor Analysis. J. Mach. Learn. Res. Dimitris Bertsimas, Martin S. Copenhaver, Rahul Mazumder
2017	J	`jnl`	The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization. IEEE Trans. Inf. Theory Rahul Mazumder, Peter Radchenko
2015	J	`jnl`	A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives. CoRR Robert M. Freund, Paul Grigas, Rahul Mazumder
2015	J	`jnl`	Matrix completion and low-rank SVD via fast alternating least squares. J. Mach. Learn. Res. Trevor Hastie, Rahul Mazumder, Jason D. Lee, Reza Zadeh
2013	J	`jnl`	AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods. CoRR Robert M. Freund, Paul Grigas, Rahul Mazumder
2013	—	`conf`	Non-negative matrix completion for bandwidth extension: A convex optimization approach. MLSP Dennis L. Sun, Rahul Mazumder
2012	J	`jnl`	Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso. J. Mach. Learn. Res. Rahul Mazumder, Trevor Hastie
2011	J	`jnl`	The Graphical Lasso: New Insights and Alternatives CoRR Rahul Mazumder, Trevor Hastie
2010	J	`jnl`	Spectral Regularization Algorithms for Learning Large Incomplete Matrices. J. Mach. Learn. Res. Rahul Mazumder, Trevor Hastie, Robert Tibshirani