Rahul Mazumder
26 papers · 2010–2026 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (38) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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Deep Specialist
(11)
👥
Mega-Team · Squad
🧬
Topic Evolution
🧭
Keyword Pioneer
🗃️
Keyword Collector
(130)
❓
The Questioner
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Unstoppable · Bronze
💎
Century Club · Bronze
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Prolific Year · Productive
Top co-authors
Research topics
Machine Learning
(26)
Mathematics & Optimization
(14)
Core Methods
(14)
Optimization
(14)
Optimization & Theory · Machine Learning
(13)
Application Areas
(10)
Deep Learning
(8)
Optimization & Theory · Deep Learning
(7)
Artificial Intelligence
(5)
Core AI
(5)
Learning Types · Machine Learning
(5)
Architectures
(3)
Learning Types · Deep Learning
(1)
Mathematics
(1)
Models
(1)
Keywords
model compression
(5)
combinatorial optimization
(4)
structured pruning
(3)
convex optimization
(3)
feature selection
(3)
tree ensemble
(3)
model pruning
(3)
random forest
(2)
large language model
(2)
nuclear norm
(2)
decision tree
(2)
coordinate descent
(2)
l0 regularization
(2)
low-rank approximation
(2)
matrix completion
(2)
sparsity constraint
(2)
variable selection
(2)
linear programming
(2)
model quantization
(2)
neural network
(2)
Papers
Theoretical Compression Bounds for Wide Multilayer Perceptrons
COLT 2026
Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
ICLR 2025
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
JMLR 2025
Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems
EMNLP 2025
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models
NeurIPS 2024
End-to-end Feature Selection Approach for Learning Skinny Trees
AISTATS 2024
FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning
AISTATS 2024
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
ICML 2024
Sparse NMF with Archetypal Regularization: Computational and Robustness Properties
JMLR 2024
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
ICML 2023
ForestPrune: Compact Depth-Pruned Tree Ensembles
AISTATS 2023
GRAND-SLAMIN’ Interpretable Additive Modeling with Structural Constraints
NeurIPS 2023
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization
JMLR 2023
On the Convergence of CART under Sufficient Impurity Decrease Condition
NeurIPS 2023
Pushing the limits of fairness impossibility: Who's the fairest of them all?
NeurIPS 2022
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features
ICML 2022
Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation
JMLR 2022
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning
NeurIPS 2021
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives
JMLR 2021
ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications
ICML 2020
Learning Hierarchical Interactions at Scale: A Convex Optimization Approach
AISTATS 2020
The Tree Ensemble Layer: Differentiability meets Conditional Computation
ICML 2020
Certifiably Optimal Low Rank Factor Analysis
JMLR 2017
Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares
JMLR 2015
Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso
JMLR 2012
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
JMLR 2010