← Authors

Elad Hazan

96 papers · 2007–2025 · 8 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (25) 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (8) 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (36) 🀝 Dynamic Duo (14) πŸ”¬ Deep Specialist (16) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) ⚑ Prolific Year (8) πŸ”₯ Unstoppable (15) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (131) πŸ’Ž Century Club (96) πŸ“ˆ Trend Setter

Conferences

NIPS (36) ICML (21) COLT (19) JMLR (6) ALT (5) L4DC (5) ICLR (3) CORL (1)

Top co-authors

Karan Singh (14) Satyen Kale (12) Xinyi Chen (12) Naman Agarwal (11) Nataly Brukhim (6) Udaya Ghai (6) Tomer Koren (5) Brian Bullins (5) Zhou Lu (5) Cyril Zhang (5)

Research topics

Differential Privacy (1)

Keywords

online learning (30) regret bound (27) regret minimization (17) convex optimization (15) online convex optimization (13) stochastic optimization (12) linear dynamical system (11) online control (10) non-convex optimization (7) gradient descent (5) sublinear regret (5) bandit feedback (4) frank-wolfe algorithm (4) bandit convex optimization (4) optimal control (4) online algorithm (4) multi-armed bandit (4) convergence rate (4) low-rank matrix (3) adversarial learning (3)

Papers

Provable Length Generalization in Sequence Prediction via Spectral Filtering ICML 2025
Online Control in Population Dynamics NIPS 2024
Open Problem: Black-Box Reductions and Adaptive Gradient Methods for Nonconvex Optimization COLT 2024
Second Order Methods for Bandit Optimization and Control COLT 2024
Adaptive Regret for Bandits Made Possible: Two Queries Suffice ICLR 2024
Online Learning for Obstacle Avoidance CORL 2023
Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions NIPS 2023
Online Control for Meta-optimization NIPS 2023
Partial Matrix Completion NIPS 2023
Optimal Rates for Bandit Nonstochastic Control NIPS 2023
Online Nonstochastic Model-Free Reinforcement Learning NIPS 2023
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret L4DC 2023
Regret Guarantees for Online Deep Control L4DC 2023
Adaptive Regret for Control of Time-Varying Dynamics L4DC 2023
Projection-free Adaptive Regret with Membership Oracles ALT 2023
A Regret Minimization Approach to Multi-Agent Control ICML 2022
Non-convex online learning via algorithmic equivalence NIPS 2022
A Boosting Approach to Reinforcement Learning NIPS 2022
Robust Online Control with Model Misspecification L4DC 2022
Multiclass Boosting and the Cost of Weak Learning NIPS 2021
Online Control of Unknown Time-Varying Dynamical Systems NIPS 2021
Generating Adversarial Disturbances for Controller Verification L4DC 2021
Boosting for Online Convex Optimization ICML 2021
Online Boosting with Bandit Feedback ALT 2021
Black-Box Control for Linear Dynamical Systems COLT 2021
A Regret Minimization Approach to Iterative Learning Control ICML 2021
Faster Projection-free Online Learning COLT 2020
Online Agnostic Boosting via Regret Minimization NIPS 2020
Geometric Exploration for Online Control NIPS 2020
Non-Stochastic Control with Bandit Feedback NIPS 2020
Boosting for Control of Dynamical Systems ICML 2020
Extreme Tensoring for Low-Memory Preconditioning ICLR 2020
Exponentiated Gradient Meets Gradient Descent ALT 2020
The Nonstochastic Control Problem ALT 2020
Improper Learning for Non-Stochastic Control COLT 2020
The Gradient Complexity of Linear Regression COLT 2020
Private Learning Implies Online Learning: An Efficient Reduction NIPS 2019
Logarithmic Regret for Online Control NIPS 2019
Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning ALT 2019
Provably Efficient Maximum Entropy Exploration ICML 2019
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
Online Learning of Quantum States NIPS 2018
Spectral Filtering for General Linear Dynamical Systems NIPS 2018
Lower Bounds for Higher-Order Convex Optimization COLT 2018
Open problem: Improper learning of mixtures of Gaussians COLT 2018
Hyperparameter optimization: a spectral approach ICLR 2018
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization ICML 2018
Online Improper Learning with an Approximation Oracle NIPS 2018
Second-Order Stochastic Optimization for Machine Learning in Linear Time JMLR 2017
Efficient Regret Minimization in Non-Convex Games ICML 2017
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls NIPS 2017
Learning Linear Dynamical Systems via Spectral Filtering NIPS 2017
A Non-generative Framework and Convex Relaxations for Unsupervised Learning NIPS 2016
The Limits of Learning with Missing Data NIPS 2016
Online Learning with Low Rank Experts COLT 2016
Optimal Black-Box Reductions Between Optimization Objectives NIPS 2016
Variance-Reduced and Projection-Free Stochastic Optimization ICML 2016
Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier ICML 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning ICML 2016
Volumetric Spanners: An Efficient Exploration Basis for Learning JMLR 2016
Variance Reduction for Faster Non-Convex Optimization ICML 2016
On Graduated Optimization for Stochastic Non-Convex Problems ICML 2016
Beyond Convexity: Stochastic Quasi-Convex Optimization NIPS 2015
Conference on Learning Theory 2015: Preface COLT 2015
Classification with Low Rank and Missing Data ICML 2015
Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets ICML 2015
Online Learning of Eigenvectors ICML 2015
Online Time Series Prediction with Missing Data ICML 2015
Online Gradient Boosting NIPS 2015
Online Learning for Adversaries with Memory: Price of Past Mistakes NIPS 2015
Volumetric Spanners: an Efficient Exploration Basis for Learning COLT 2014
Bandit Convex Optimization: Towards Tight Bounds NIPS 2014
The Blinded Bandit: Learning with Adaptive Feedback NIPS 2014
Hard-Margin Active Linear Regression ICML 2014
Beyond the Regret Minimization Barrier: Optimal Algorithms for Stochastic Strongly-Convex Optimization JMLR 2014
Logistic Regression: Tight Bounds for Stochastic and Online Optimization COLT 2014
Better Rates for Any Adversarial Deterministic MDP ICML 2013
Online Learning for Time Series Prediction COLT 2013
Online Submodular Minimization JMLR 2012
Near-Optimal Algorithms for Online Matrix Prediction COLT 2012
A Polylog Pivot Steps Simplex Algorithm for Classification NIPS 2012
(weak) Calibration is Computationally Hard COLT 2012
A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011
Beating SGD: Learning SVMs in Sublinear Time NIPS 2011
Blackwell Approachability and No-Regret Learning are Equivalent COLT 2011
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011
Approximating Semidefinite Programs in Sublinear Time NIPS 2011
Better Algorithms for Benign Bandits JMLR 2011
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization JMLR 2011
Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction NIPS 2011
Beyond Convexity: Online Submodular Minimization NIPS 2009
On Stochastic and Worst-case Models for Investing NIPS 2009
Adaptive Online Gradient Descent NIPS 2007
Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria NIPS 2007