Naman Agarwal
25 papers · 2017–2025 · 7 venues · across top CS/AI venues
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Achievements
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Deep Specialist
(12)
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(11)
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Triple Crown
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Keyword Pioneer
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Century Club Β· Bronze
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Unstoppable Β· Bronze
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Keyword Collector
(119)
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Top co-authors
Research topics
Machine Learning
(23)
Optimization & Theory Β· Machine Learning
(20)
Mathematics & Optimization
(12)
Optimization
(12)
Learning Types Β· Machine Learning
(7)
Deep Learning
(6)
Application Areas
(5)
Artificial Intelligence
(4)
Reinforcement Learning
(4)
Methods
(4)
Core AI
(3)
Core Methods
(3)
Optimization & Theory Β· Deep Learning
(3)
Learning Paradigms
(2)
Learning Types Β· Deep Learning
(2)
Keywords
regret bound
(7)
online control
(4)
convex optimization
(4)
linear dynamical system
(4)
differential privacy
(4)
online learning
(3)
stochastic optimization
(3)
sample complexity
(3)
empirical risk minimization
(2)
low-rank matrix
(2)
regret minimization
(2)
non-convex optimization
(2)
online convex optimization
(2)
batch normalization
(1)
collaborative filtering
(1)
adversarial learning
(1)
policy gradient
(1)
game theory
(1)
stochastic gradient descent
(1)
neural network optimization
(1)
Papers
Provable Length Generalization in Sequence Prediction via Spectral Filtering
ICML 2025
Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements
ICML 2024
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret
L4DC 2023
Differentially Private and Lazy Online Convex Optimization
COLT 2023
Multi-User Reinforcement Learning with Low Rank Rewards
ICML 2023
Variance-Reduced Conservative Policy Iteration
ALT 2023
Efficient Methods for Online Multiclass Logistic Regression
ALT 2022
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs
ICLR 2022
Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States
COLT 2022
Acceleration via Fractal Learning Rate Schedules
ICML 2021
A Deep Conditioning Treatment of Neural Networks
ALT 2021
A Regret Minimization Approach to Iterative Learning Control
ICML 2021
The Skellam Mechanism for Differentially Private Federated Learning
NeurIPS 2021
Boosting for Control of Dynamical Systems
ICML 2020
Extreme Tensoring for Low-Memory Preconditioning
ICLR 2020
Leverage Score Sampling for Faster Accelerated Regression and ERM
ALT 2020
Stochastic Optimization with Laggard Data Pipelines
NeurIPS 2020
Efficient Full-Matrix Adaptive Regularization
ICML 2019
Learning in Non-convex Games with an Optimization Oracle
COLT 2019
Logarithmic Regret for Online Control
NeurIPS 2019
Online Control with Adversarial Disturbances
ICML 2019
cpSGD: Communication-efficient and differentially-private distributed SGD
NeurIPS 2018
Lower Bounds for Higher-Order Convex Optimization
COLT 2018
Second-Order Stochastic Optimization for Machine Learning in Linear Time
JMLR 2017
The Price of Differential Privacy for Online Learning
ICML 2017