Elad Hazan

According to our database1, Elad Hazan authored at least 148 papers between 2003 and 2022.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

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Bibliography

2022
Efficient Adaptive Regret Minimization.
CoRR, 2022

Adaptive Online Learning of Quantum States.
CoRR, 2022

Non-convex online learning via algorithmic equivalence.
CoRR, 2022

Adaptive Gradient Methods with Local Guarantees.
CoRR, 2022

A Regret Minimization Approach to Multi-Agent Contro.
CoRR, 2022

Robust Online Control with Model Misspecification.
Proceedings of the Learning for Dynamics and Control Conference, 2022

A Regret Minimization Approach to Multi-Agent Control.
Proceedings of the International Conference on Machine Learning, 2022

2021
Machine Learning for Mechanical Ventilation Control (Extended Abstract).
CoRR, 2021

Provable Regret Bounds for Deep Online Learning and Control.
CoRR, 2021

A Boosting Approach to Reinforcement Learning.
CoRR, 2021

Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking.
CoRR, 2021

Machine Learning for Mechanical Ventilation Control.
CoRR, 2021

Boosting simple learners.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Online Control of Unknown Time-Varying Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multiclass Boosting and the Cost of Weak Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Generating Adversarial Disturbances for Controller Verification.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Boosting for Online Convex Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Regret Minimization Approach to Iterative Learning Control.
Proceedings of the 38th International Conference on Machine Learning, 2021

Black-Box Control for Linear Dynamical Systems.
Proceedings of the Conference on Learning Theory, 2021

Online Boosting with Bandit Feedback.
Proceedings of the Algorithmic Learning Theory, 2021

2020
Adaptive Regret for Control of Time-Varying Dynamics.
CoRR, 2020

Disentangling Adaptive Gradient Methods from Learning Rates.
CoRR, 2020

Geometric Exploration for Online Control.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Non-Stochastic Control with Bandit Feedback.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Agnostic Boosting via Regret Minimization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Boosting for Control of Dynamical Systems.
Proceedings of the 37th International Conference on Machine Learning, 2020

Extreme Tensoring for Low-Memory Preconditioning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Improper Learning for Non-Stochastic Control.
Proceedings of the Conference on Learning Theory, 2020

Faster Projection-free Online Learning.
Proceedings of the Conference on Learning Theory, 2020

The Gradient Complexity of Linear Regression.
Proceedings of the Conference on Learning Theory, 2020

The Nonstochastic Control Problem.
Proceedings of the Algorithmic Learning Theory, 2020

Exponentiated Gradient Meets Gradient Descent.
Proceedings of the Algorithmic Learning Theory, 2020

2019
Lecture Notes: Optimization for Machine Learning.
CoRR, 2019

Boosting for Dynamical Systems.
CoRR, 2019

Private Learning Implies Online Learning: An Efficient Reduction.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Logarithmic Regret for Online Control.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Provably Efficient Maximum Entropy Exploration.
Proceedings of the 36th International Conference on Machine Learning, 2019

Online Control with Adversarial Disturbances.
Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient Full-Matrix Adaptive Regularization.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning in Non-convex Games with an Optimization Oracle.
Proceedings of the Conference on Learning Theory, 2019

Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning.
Proceedings of the Algorithmic Learning Theory, 2019

2018
Learning in Non-convex Games with an Optimization Oracle.
CoRR, 2018

The Case for Full-Matrix Adaptive Regularization.
CoRR, 2018

Online Learning of Quantum States.
CoRR, 2018

Spectral Filtering for General Linear Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Improper Learning with an Approximation Oracle.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Learning of Quantum States.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization.
Proceedings of the 35th International Conference on Machine Learning, 2018

Hyperparameter optimization: a spectral approach.
Proceedings of the 6th International Conference on Learning Representations, 2018

Towards Provable Control for Unknown Linear Dynamical Systems.
Proceedings of the 6th International Conference on Learning Representations, 2018

Open problem: Improper learning of mixtures of Gaussians.
Proceedings of the Conference On Learning Theory, 2018

Lower Bounds for Higher-Order Convex Optimization.
Proceedings of the Conference On Learning Theory, 2018

2017
Second-Order Stochastic Optimization for Machine Learning in Linear Time.
J. Mach. Learn. Res., 2017

Finding approximate local minima faster than gradient descent.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Learning Linear Dynamical Systems via Spectral Filtering.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient Regret Minimization in Non-Convex Games.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
A Linearly Convergent Variant of the Conditional Gradient Algorithm under Strong Convexity, with Applications to Online and Stochastic Optimization.
SIAM J. Optim., 2016

A linear-time algorithm for trust region problems.
Math. Program., 2016

Sublinear time algorithms for approximate semidefinite programming.
Math. Program., 2016

Learning rotations with little regret.
Mach. Learn., 2016

Volumetric Spanners: An Efficient Exploration Basis for Learning.
J. Mach. Learn. Res., 2016

Introduction to Online Convex Optimization.
Found. Trends Optim., 2016

An optimal algorithm for bandit convex optimization.
CoRR, 2016

Finding Approximate Local Minima for Nonconvex Optimization in Linear Time.
CoRR, 2016

Second Order Stochastic Optimization in Linear Time.
CoRR, 2016

The computational power of optimization in online learning.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Optimal Black-Box Reductions Between Optimization Objectives.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Non-generative Framework and Convex Relaxations for Unsupervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

The Limits of Learning with Missing Data.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variance Reduction for Faster Non-Convex Optimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

On Graduated Optimization for Stochastic Non-Convex Problems.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Variance-Reduced and Projection-Free Stochastic Optimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Faster Eigenvector Computation via Shift-and-Invert Preconditioning.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Online Learning with Low Rank Experts.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Oracle-Based Robust Optimization via Online Learning.
Oper. Res., 2015

Fast and Simple PCA via Convex Optimization.
CoRR, 2015

Beyond Convexity: Stochastic Quasi-Convex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Online Gradient Boosting.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Online Learning for Adversaries with Memory: Price of Past Mistakes.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Classification with Low Rank and Missing Data.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Online Learning of Eigenvectors.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Online Time Series Prediction with Missing Data.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Conference on Learning Theory 2015: Preface.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Beyond the regret minimization barrier: optimal algorithms for stochastic strongly-convex optimization.
J. Mach. Learn. Res., 2014

Bandit Convex Optimization: Towards Tight Bounds.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

The Blinded Bandit: Learning with Adaptive Feedback.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Hard-Margin Active Linear Regression.
Proceedings of the 31th International Conference on Machine Learning, 2014

Volumetric Spanners: an Efficient Exploration Basis for Learning.
Proceedings of The 27th Conference on Learning Theory, 2014

Logistic Regression: Tight Bounds for Stochastic and Online Optimization.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Adaptive Universal Linear Filtering.
IEEE Trans. Signal Process., 2013

Online Learning for Loss Functions with Memory and Applications to Statistical Arbitrage
CoRR, 2013

A Polynomial Time Conditional Gradient Algorithm with Applications to Online and Stochastic Optimization
CoRR, 2013

Volumetric Spanners and their Applications to Machine Learning.
CoRR, 2013

Better Rates for Any Adversarial Deterministic MDP.
Proceedings of the 30th International Conference on Machine Learning, 2013

Playing Non-linear Games with Linear Oracles.
Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science, 2013

Online Learning for Time Series Prediction.
Proceedings of the COLT 2013, 2013

2012
The Multiplicative Weights Update Method: a Meta-Algorithm and Applications.
Theory Comput., 2012

Interior-Point Methods for Full-Information and Bandit Online Learning.
IEEE Trans. Inf. Theory, 2012

Near-Optimal Algorithms for Online Matrix Prediction.
Proceedings of the COLT 2012, 2012

Online submodular minimization.
J. Mach. Learn. Res., 2012

(weak) Calibration is Computationally Hard.
Proceedings of the COLT 2012, 2012

Sublinear optimization for machine learning.
J. ACM, 2012

Almost Optimal Sublinear Time Algorithm for Semidefinite Programming
CoRR, 2012

A Polylog Pivot Steps Simplex Algorithm for Classification.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Linear Regression with Limited Observation.
Proceedings of the 29th International Conference on Machine Learning, 2012

Projection-free Online Learning.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
How Hard Is It to Approximate the Best Nash Equilibrium?
SIAM J. Comput., 2011

A simple multi-armed bandit algorithm with optimal variation-bounded regret.
Proceedings of the COLT 2011, 2011

Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization.
Proceedings of the COLT 2011, 2011

Better Algorithms for Benign Bandits.
J. Mach. Learn. Res., 2011

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization.
J. Mach. Learn. Res., 2011

Blackwell Approachability and No-Regret Learning are Equivalent.
Proceedings of the COLT 2011, 2011

Universal MMSE Filtering With Logarithmic Adaptive Regret
CoRR, 2011

Optimal Algorithms for Ridge and Lasso Regression with Partially Observed Attributes
CoRR, 2011

Beating SGD: Learning SVMs in Sublinear Time.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Approximating Semidefinite Programs in Sublinear Time.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
O(sqrt(log(n)) Approximation to SPARSEST CUT in Õ(n<sup>2</sup>) Time.
SIAM J. Comput., 2010

Extracting certainty from uncertainty: regret bounded by variation in costs.
Mach. Learn., 2010

Blackwell Approachability and Low-Regret Learning are Equivalent
CoRR, 2010

On-line Variance Minimization in O(n2) per Trial?
Proceedings of the COLT 2010, 2010

2009
On Stochastic and Worst-case Models for Investing.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Beyond Convexity: Online Submodular Minimization.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Efficient learning algorithms for changing environments.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Sparse Approximate Solutions to Semidefinite Programs.
Proceedings of the LATIN 2008: Theoretical Informatics, 2008

Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Logarithmic regret algorithms for online convex optimization.
Mach. Learn., 2007

Adaptive Algorithms for Online Decision Problems.
Electron. Colloquium Comput. Complex., 2007

Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Adaptive Online Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Online Learning with Prior Knowledge.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
HAPLOFREQ-Estimating Haplotype Frequencies Efficiently.
J. Comput. Biol., 2006

Efficient Algorithms for Online Game Playing and Universal Portfolio Management.
Electron. Colloquium Comput. Complex., 2006

Approximate Convex Optimization by Online Game Playing
CoRR, 2006

On the complexity of approximating <i>k</i>-set packing.
Comput. Complex., 2006

Algorithms for portfolio management based on the Newton method.
Proceedings of the Machine Learning, 2006

Logarithmic Regret Algorithms for Online Convex Optimization.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

A Fast Random Sampling Algorithm for Sparsifying Matrices.
Proceedings of the Approximation, 2006

2005
On Non-Approximability for Quadratic Programs
Electron. Colloquium Comput. Complex., 2005

HAPLOFREQ - Estimating Haplotype Frequencies E.ciently.
Proceedings of the Research in Computational Molecular Biology, 2005

Analysis and Algorithms for Content-Based Event Matching.
Proceedings of the 25th International Conference on Distributed Computing Systems Workshops (ICDCS 2005 Workshops), 2005

Fast Algorithms for Approximate Semide.nite Programming using the Multiplicative Weights Update Method.
Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2005), 2005

2004
0(sqrt (log n)) Approximation to SPARSEST CUT in Õ(n<sup>2</sup>) Time.
Proceedings of the 45th Symposium on Foundations of Computer Science (FOCS 2004), 2004

2003
On the Hardness of Approximating k-Dimensional Matching
Electron. Colloquium Comput. Complex., 2003

On the Complexity of Approximating k-Dimensional Matching.
Proceedings of the Approximation, 2003


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