b'Tomer Koren'

research

∙ 08/28/2023

Rate-Optimal Policy Optimization for Linear Markov Decision Processes

We study regret minimization in online episodic linear Markov Decision P...

0 Uri Sherman, et al. ∙

research

∙ 03/02/2023

Tight Risk Bounds for Gradient Descent on Separable Data

We study the generalization properties of unregularized gradient methods...

0 Matan Schliserman, et al. ∙

research

∙ 02/27/2023

Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime

We consider online learning problems in the realizable setting, where th...

0 Hilal Asi, et al. ∙

research

∙ 02/17/2023

SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance

We study Stochastic Gradient Descent with AdaGrad stepsizes: a popular a...

0 Amit Attia, et al. ∙

research

∙ 01/30/2023

Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation

We study reinforcement learning with linear function approximation and a...

0 Uri Sherman, et al. ∙

research

∙ 10/24/2022

Private Online Prediction from Experts: Separations and Faster Rates

Online prediction from experts is a fundamental problem in machine learn...

0 Hilal Asi, et al. ∙

research

∙ 07/28/2022

Regret Minimization and Convergence to Equilibria in General-sum Markov Games

An abundance of recent impossibility results establish that regret minim...

0 Liad Erez, et al. ∙

research

∙ 07/17/2022

Uniform Stability for First-Order Empirical Risk Minimization

We consider the problem of designing uniformly stable first-order optimi...

0 Amit Attia, et al. ∙

research

∙ 06/07/2022

Better Best of Both Worlds Bounds for Bandits with Switching Costs

We study best-of-both-worlds algorithms for bandits with switching cost,...

0 Idan Amir, et al. ∙

research

∙ 06/03/2022

Rate-Optimal Online Convex Optimization in Adaptive Linear Control

We consider the problem of controlling an unknown linear dynamical syste...

8 Asaf Cassel, et al. ∙

research

∙ 03/02/2022

Efficient Online Linear Control with Stochastic Convex Costs and Unknown Dynamics

We consider the problem of controlling an unknown linear dynamical syste...

3 Asaf Cassel, et al. ∙

research

∙ 02/27/2022

Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond

An influential line of recent work has focused on the generalization pro...

0 Matan Schliserman, et al. ∙

research

∙ 02/27/2022

Benign Underfitting of Stochastic Gradient Descent

We study to what extent may stochastic gradient descent (SGD) be underst...

0 Tomer Koren, et al. ∙

research

∙ 07/20/2021

Best-of-All-Worlds Bounds for Online Learning with Feedback Graphs

We study the online learning with feedback graphs framework introduced b...

0 Liad Erez, et al. ∙

research

∙ 06/29/2021

Never Go Full Batch (in Stochastic Convex Optimization)

We study the generalization performance of full-batch optimization algor...

0 Idan Amir, et al. ∙

research

∙ 06/29/2021

Optimal Rates for Random Order Online Optimization

We study online convex optimization in the random order model, recently ...

0 Uri Sherman, et al. ∙

research

∙ 06/22/2021

Asynchronous Stochastic Optimization Robust to Arbitrary Delays

We consider stochastic optimization with delayed gradients where, at eac...

10 Alon Cohen, et al. ∙

research

∙ 06/04/2021

Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions

We study the stochastic Multi-Armed Bandit (MAB) problem with random del...

0 Tal Lancewicki, et al. ∙

research

∙ 03/02/2021

Private Stochastic Convex Optimization: Optimal Rates in ℓ_1 Geometry

Stochastic convex optimization over an ℓ_1-bounded domain is ubiquitous ...

0 Hilal Asi, et al. ∙

research

∙ 02/25/2021

Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with √(T) Regret

We consider the task of learning to control a linear dynamical system un...

0 Asaf Cassel, et al. ∙

research

∙ 02/24/2021

Multiplicative Reweighting for Robust Neural Network Optimization

Deep neural networks are widespread due to their powerful performance. Y...

0 Noga Bar, et al. ∙

research

∙ 02/07/2021

Lazy OCO: Online Convex Optimization on a Switching Budget

We study a variant of online convex optimization where the player is per...

0 Uri Sherman, et al. ∙

research

∙ 02/03/2021

The Instability of Accelerated Gradient Descent

We study the algorithmic stability of Nesterov's accelerated gradient me...

0 Amit Attia, et al. ∙

research

∙ 02/01/2021

SGD Generalizes Better Than GD (And Regularization Doesn't Help)

We give a new separation result between the generalization performance o...

0 Idan Amir, et al. ∙

research

∙ 01/31/2021

Online Markov Decision Processes with Aggregate Bandit Feedback

We study a novel variant of online finite-horizon Markov Decision Proces...

10 Alon Cohen, et al. ∙

research

∙ 10/27/2020

Adversarial Dueling Bandits

We introduce the problem of regret minimization in Adversarial Dueling B...

0 Aadirupa Saha, et al. ∙

research

∙ 10/26/2020

Stochastic Optimization with Laggard Data Pipelines

State-of-the-art optimization is steadily shifting towards massively par...

20 Naman Agarwal, et al. ∙

research

∙ 08/11/2020

Holdout SGD: Byzantine Tolerant Federated Learning

This work presents a new distributed Byzantine tolerant federated learni...

0 Shahar Azulay, et al. ∙

research

∙ 07/01/2020

Bandit Linear Control

We consider the problem of controlling a known linear dynamical system u...

0 Asaf Cassel, et al. ∙

research

∙ 05/10/2020

Private Stochastic Convex Optimization: Optimal Rates in Linear Time

We study differentially private (DP) algorithms for stochastic convex op...

38 Vitaly Feldman, et al. ∙

research

∙ 03/13/2020

Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study

The notion of implicit bias, or implicit regularization, has been sugges...

0 Assaf Dauber, et al. ∙

research

∙ 02/26/2020

Disentangling Adaptive Gradient Methods from Learning Rates

We investigate several confounding factors in the evaluation of optimiza...

6 Naman Agarwal, et al. ∙

research

∙ 02/24/2020

Prediction with Corrupted Expert Advice

We revisit the fundamental problem of prediction with expert advice, in ...

0 Idan Amir, et al. ∙

research

∙ 02/20/2020

Second Order Optimization Made Practical

Optimization in machine learning, both theoretical and applied, is prese...

16 Rohan Anil, et al. ∙

research

∙ 02/19/2020

Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently

We consider the problem of learning in Linear Quadratic Control systems ...

4 Asaf Cassel, et al. ∙

research

∙ 06/08/2019

Robust Bi-Tempered Logistic Loss Based on Bregman Divergences

We introduce a temperature into the exponential function and replace the...

1 Ehsan Amid, et al. ∙

research

∙ 04/23/2019

Semi-Cyclic Stochastic Gradient Descent

We consider convex SGD updates with a block-cyclic structure, i.e. where...

0 Hubert Eichner, et al. ∙

research

∙ 02/22/2019

Better Algorithms for Stochastic Bandits with Adversarial Corruptions

We study the stochastic multi-armed bandits problem in the presence of a...

0 Anupam Gupta, et al. ∙

research

∙ 02/17/2019

Learning Linear-Quadratic Regulators Efficiently with only √(T) Regret

We present the first computationally-efficient algorithm with O(√(T)) r...

0 Alon Cohen, et al. ∙

research

∙ 01/30/2019

Memory-Efficient Adaptive Optimization for Large-Scale Learning

Adaptive gradient-based optimizers such as AdaGrad and Adam are among th...

1 Rohan Anil, et al. ∙

research

∙ 06/19/2018

Online Linear Quadratic Control

We study the problem of controlling linear time-invariant systems with k...

0 Alon Cohen, et al. ∙

research

∙ 02/26/2018

Shampoo: Preconditioned Stochastic Tensor Optimization

Preconditioned gradient methods are among the most general and powerful ...

0 Vineet Gupta, et al. ∙

research

∙ 06/20/2017

A Unified Approach to Adaptive Regularization in Online and Stochastic Optimization

We describe a framework for deriving and analyzing online optimization a...

0 Vineet Gupta, et al. ∙

research

∙ 05/23/2016

Online Learning with Feedback Graphs Without the Graphs

We study an online learning framework introduced by Mannor and Shamir (2...

0 Alon Cohen, et al. ∙

research

∙ 06/18/2012

Linear Regression with Limited Observation

We consider the most common variants of linear regression, including Rid...

0 Elad Hazan, et al. ∙

Tomer Koren

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