Rahul Mazumder

Orcid: 0000-0003-1384-9743

According to our database1, Rahul Mazumder authored at least 69 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A new computational framework for log-concave density estimation.
Math. Program. Comput., June, 2024

Subgradient Regularized Multivariate Convex Regression at Scale.
SIAM J. Optim., 2024

Sparse NMF with Archetypal Regularization: Computational and Robustness Properties.
J. Mach. Learn. Res., 2024

ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models.
CoRR, 2024

Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests.
CoRR, 2024

FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference.
CoRR, 2024

FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML.
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.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

End-to-end Feature Selection Approach for Learning Skinny Trees.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Linear regression with partially mismatched data: local search with theoretical guarantees.
Math. Program., February, 2023

Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low.
Oper. Res., January, 2023

L0Learn: A Scalable Package for Sparse Learning using L0 Regularization.
J. Mach. Learn. Res., 2023

QuantEase: Optimization-based Quantization for Language Models - An Efficient and Intuitive Algorithm.
CoRR, 2023

Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives.
CoRR, 2023

Matrix Completion from General Deterministic Sampling Patterns.
CoRR, 2023

Sharpness-Aware Minimization: An Implicit Regularization Perspective.
CoRR, 2023

mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization.
CoRR, 2023

Promoting Inactive Members in Edge-Building Marketplace.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

On the Convergence of CART under Sufficient Impurity Decrease Condition.
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.
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.
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.
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.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Fast as CHITA: Neural Network Pruning with Combinatorial Optimization.
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.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Dynamic Covariance Estimation under Structural Assumptions via a Joint Optimization Approach.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Optimizing for Member Value in an Edge Building Marketplace.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

ForestPrune: Compact Depth-Pruned Tree Ensembles.
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.
SIAM J. Optim., December, 2022

Sparse regression at scale: branch-and-bound rooted in first-order optimization.
Math. Program., 2022

Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation.
J. Mach. Learn. Res., 2022

Using ℓ1-Relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA.
Oper. Res., 2022

Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization.
CoRR, 2022

ForestPrune: Compact Depth-Controlled Tree Ensembles.
CoRR, 2022

Newer is Not Always Better: Rethinking Transferability Metrics, Their Peculiarities, Stability and Performance.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Pushing the limits of fairness impossibility: Who's the fairest of them all?
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2021
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives.
J. Mach. Learn. Res., 2021

Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation.
CoRR, 2021

Predicting Census Survey Response Rates via Interpretable Nonparametric Additive Models with Structured Interactions.
CoRR, 2021

Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives.
CoRR, 2021

Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification.
CoRR, 2021

DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning.
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.
Proceedings of the Integer Programming and Combinatorial Optimization, 2021

2020
Randomized Gradient Boosting Machine.
SIAM J. Optim., 2020

Matrix completion with nonconvex regularization: spectral operators and scalable algorithms.
Stat. Comput., 2020

Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms.
Oper. Res., 2020

The Tree Ensemble Layer: Differentiability meets Conditional Computation.
Proceedings of the 37th International Conference on Machine Learning, 2020

ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning Hierarchical Interactions at Scale: A Convex Optimization Approach.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Learning a Mixture of Gaussians via Mixed-Integer Optimization.
INFORMS J. Optim., July, 2019

Computation of the maximum likelihood estimator in low-rank factor analysis.
Math. Program., 2019

Solving large-scale L1-regularized SVMs and cousins: the surprising effectiveness of column and constraint generation.
CoRR, 2019

2018
Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods.
CoRR, 2018

Hierarchical Modeling and Shrinkage for User Session Length Prediction in Media Streaming.
CoRR, 2018

Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming.
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.
IEEE Trans. Inf. Theory, 2017

An Extended Frank-Wolfe Method with "In-Face" Directions, and Its Application to Low-Rank Matrix Completion.
SIAM J. Optim., 2017

Certifiably Optimal Low Rank Factor Analysis.
J. Mach. Learn. Res., 2017

2015
Matrix completion and low-rank SVD via fast alternating least squares.
J. Mach. Learn. Res., 2015

A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives.
CoRR, 2015

2013
AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods.
CoRR, 2013

Non-negative matrix completion for bandwidth extension: A convex optimization approach.
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.
J. Mach. Learn. Res., 2012

2011
The Graphical Lasso: New Insights and Alternatives
CoRR, 2011

2010
Spectral Regularization Algorithms for Learning Large Incomplete Matrices.
J. Mach. Learn. Res., 2010


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