Naman Agarwal
25 papers · 2017–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (8)
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(36)
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Conference Polyglot
(7)
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Academic Marathon
(8)
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Dynamic Duo
(11)
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Triple Crown
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Deep Specialist
(11)
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Keyword Collector
(98)
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Trend Setter
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Century Club
(25)
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Unstoppable
(9)
Conferences
ICML (9)
ALT (4)
COLT (4)
NIPS (4)
ICLR (2)
JMLR (1)
L4DC (1)
Top co-authors
Research topics
Keywords
regret bound
(6)
differential privacy
(4)
online control
(4)
convex optimization
(4)
online learning
(3)
linear dynamical system
(3)
stochastic optimization
(2)
empirical risk minimization
(2)
non-convex optimization
(2)
sample complexity
(2)
regret minimization
(2)
low-rank matrix
(2)
convergence analysis
(1)
batch normalization
(1)
collaborative filtering
(1)
policy gradient
(1)
adversarial learning
(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
Multi-User Reinforcement Learning with Low Rank Rewards
ICML 2023
Variance-Reduced Conservative Policy Iteration
ALT 2023
Differentially Private and Lazy Online Convex Optimization
COLT 2023
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret
L4DC 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
The Skellam Mechanism for Differentially Private Federated Learning
NIPS 2021
A Regret Minimization Approach to Iterative Learning Control
ICML 2021
Acceleration via Fractal Learning Rate Schedules
ICML 2021
A Deep Conditioning Treatment of Neural Networks
ALT 2021
Extreme Tensoring for Low-Memory Preconditioning
ICLR 2020
Stochastic Optimization with Laggard Data Pipelines
NIPS 2020
Leverage Score Sampling for Faster Accelerated Regression and ERM
ALT 2020
Boosting for Control of Dynamical Systems
ICML 2020
Online Control with Adversarial Disturbances
ICML 2019
Efficient Full-Matrix Adaptive Regularization
ICML 2019
Learning in Non-convex Games with an Optimization Oracle
COLT 2019
Logarithmic Regret for Online Control
NIPS 2019
Lower Bounds for Higher-Order Convex Optimization
COLT 2018
cpSGD: Communication-efficient and differentially-private distributed SGD
NIPS 2018
Second-Order Stochastic Optimization for Machine Learning in Linear Time
JMLR 2017
The Price of Differential Privacy for Online Learning
ICML 2017