Rahul Mazumder
25 papers · 2010–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (13) π§ Keyword Pioneer π Conference Polyglot (6)
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Cross-Pollinator
(10)
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Keyword Pioneer
π₯
Mega-Team
(20)
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Keyword Champion
(3)
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Deep Specialist
(11)
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Topic Evolution
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Century Club
(25)
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Prolific Year
(5)
ποΈ
Keyword Collector
(56)
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The Questioner
π₯
Unstoppable
(6)
Conferences
JMLR (9)
ICML (5)
NIPS (5)
AISTATS (4)
EMNLP (1)
ICLR (1)
Top co-authors
Keywords
model compression
(5)
tree ensemble
(3)
feature selection
(3)
convex optimization
(3)
combinatorial optimization
(3)
coordinate descent
(2)
neural network
(2)
variable selection
(2)
decision tree
(2)
sparsity constraint
(2)
matrix completion
(2)
random forest
(2)
linear programming
(2)
nuclear norm
(2)
l0 regularization
(2)
low-rank approximation
(2)
gradient-based optimization
(1)
algorithmic fairness
(1)
sparse learning
(1)
matrix factorization
(1)
Papers
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
JMLR 2025
Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
ICLR 2025
Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems
EMNLP 2025
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
ICML 2024
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models
NIPS 2024
End-to-end Feature Selection Approach for Learning Skinny Trees
AISTATS 2024
FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning
AISTATS 2024
Sparse NMF with Archetypal Regularization: Computational and Robustness Properties
JMLR 2024
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
ICML 2023
On the Convergence of CART under Sufficient Impurity Decrease Condition
NIPS 2023
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization
JMLR 2023
GRAND-SLAMINβ Interpretable Additive Modeling with Structural Constraints
NIPS 2023
ForestPrune: Compact Depth-Pruned Tree Ensembles
AISTATS 2023
Pushing the limits of fairness impossibility: Who's the fairest of them all?
NIPS 2022
Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation
JMLR 2022
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features
ICML 2022
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning
NIPS 2021
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives
JMLR 2021
Learning Hierarchical Interactions at Scale: A Convex Optimization Approach
AISTATS 2020
The Tree Ensemble Layer: Differentiability meets Conditional Computation
ICML 2020
ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications
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