Tomer Koren

According to our database, Tomer Koren authored at least 84 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of two.

2024

A Note on High-Probability Analysis of Algorithms with Exponential, Sub-Gaussian, and General Light Tails.

Amit Attia, Tomer Koren

CoRR, 2024

How Free is Parameter-Free Stochastic Optimization?

Amit Attia, Tomer Koren

CoRR, 2024

The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization.

Matan Schliserman, Uri Sherman, Tomer Koren

CoRR, 2024

2023

Faster Convergence with Multiway Preferences.

Aadirupa Saha, Vitaly Feldman, Tomer Koren, Yishay Mansour

CoRR, 2023

Locally Optimal Descent for Dynamic Stepsize Scheduling.

Gilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain

CoRR, 2023

Rate-Optimal Policy Optimization for Linear Markov Decision Processes.

Uri Sherman, Alon Cohen, Tomer Koren, Yishay Mansour

CoRR, 2023

Tight Risk Bounds for Gradient Descent on Separable Data.

Matan Schliserman, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation.

Uri Sherman, Tomer Koren, Yishay Mansour

Proceedings of the International Conference on Machine Learning, 2023

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

Liad Erez, Tal Lancewicki, Uri Sherman, Tomer Koren, Yishay Mansour

Proceedings of the International Conference on Machine Learning, 2023

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

Amit Attia, Tomer Koren

Proceedings of the International Conference on Machine Learning, 2023

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

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

Proceedings of the International Conference on Machine Learning, 2023

Private Online Prediction from Experts: Separations and Faster Rates.

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Dueling Convex Optimization with General Preferences.

Aadirupa Saha, Tomer Koren, Yishay Mansour

CoRR, 2022

Benign Underfitting of Stochastic Gradient Descent.

Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Rate-Optimal Online Convex Optimization in Adaptive Linear Control.

Asaf B. Cassel, Alon Peled-Cohen, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Better Best of Both Worlds Bounds for Bandits with Switching Costs.

Idan Amir, Guy Azov, Tomer Koren, Roi Livni

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Matan Schliserman, Tomer Koren

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Efficient Online Linear Control with Stochastic Convex Costs and Unknown Dynamics.

Asaf B. Cassel, Alon Cohen, Tomer Koren

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Uniform Stability for First-Order Empirical Risk Minimization.

Amit Attia, Tomer Koren

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

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

Liad Erez, Tomer Koren

CoRR, 2021

Private Stochastic Convex Optimization: Optimal Rates in 𝓁₁ Geometry.

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

CoRR, 2021

Multiplicative Reweighting for Robust Neural Network Optimization.

Noga Bar, Tomer Koren, Raja Giryes

CoRR, 2021

The Instability of Accelerated Gradient Descent.

Amit Attia, Tomer Koren

CoRR, 2021

Optimal Rates for Random Order Online Optimization.

Uri Sherman, Tomer Koren, Yishay Mansour

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Best-of-All-Worlds Online Learning with Feedback Graphs.

Liad Erez, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Asynchronous Stochastic Optimization Robust to Arbitrary Delays.

Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Algorithmic Instabilities of Accelerated Gradient Descent.

Amit Attia, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Never Go Full Batch (in Stochastic Convex Optimization).

Idan Amir, Yair Carmon, Tomer Koren, Roi Livni

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dueling Convex Optimization.

Aadirupa Saha, Tomer Koren, Yishay Mansour

Proceedings of the 38th International Conference on Machine Learning, 2021

Adversarial Dueling Bandits.

Aadirupa Saha, Tomer Koren, Yishay Mansour

Proceedings of the 38th International Conference on Machine Learning, 2021

Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions.

Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour

Proceedings of the 38th International Conference on Machine Learning, 2021

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

Asaf B. Cassel, Tomer Koren

Proceedings of the 38th International Conference on Machine Learning, 2021

Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry.

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

Proceedings of the 38th International Conference on Machine Learning, 2021

Lazy OCO: Online Convex Optimization on a Switching Budget.

Uri Sherman, Tomer Koren

Proceedings of the Conference on Learning Theory, 2021

Online Markov Decision Processes with Aggregate Bandit Feedback.

Alon Cohen, Haim Kaplan, Tomer Koren, Yishay Mansour

Proceedings of the Conference on Learning Theory, 2021

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

Idan Amir, Tomer Koren, Roi Livni

Proceedings of the Conference on Learning Theory, 2021

2020

Holdout SGD: Byzantine Tolerant Federated Learning.

Shahar Azulay, Lior Raz, Amir Globerson, Tomer Koren, Yehuda Afek

CoRR, 2020

Disentangling Adaptive Gradient Methods from Learning Rates.

Naman Agarwal, Rohan Anil, Elad Hazan, Tomer Koren, Cyril Zhang

CoRR, 2020

Second Order Optimization Made Practical.

Rohan Anil, Vineet Gupta, Tomer Koren, Kevin Regan, Yoram Singer

CoRR, 2020

Private stochastic convex optimization: optimal rates in linear time.

Vitaly Feldman, Tomer Koren, Kunal Talwar

Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

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

Assaf Dauber, Meir Feder, Tomer Koren, Roi Livni

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bandit Linear Control.

Asaf B. Cassel, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Prediction with Corrupted Expert Advice.

Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stochastic Optimization with Laggard Data Pipelines.

Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently.

Asaf B. Cassel, Alon Cohen, Tomer Koren

Proceedings of the 37th International Conference on Machine Learning, 2020

Open Problem: Tight Convergence of SGD in Constant Dimension.

Tomer Koren, Shahar Segal

Proceedings of the Conference on Learning Theory, 2020

2019

Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret.

Alon Cohen, Tomer Koren, Yishay Mansour

CoRR, 2019

Memory-Efficient Adaptive Optimization for Large-Scale Learning.

Rohan Anil, Vineet Gupta, Tomer Koren, Yoram Singer

CoRR, 2019

Memory Efficient Adaptive Optimization.

Rohan Anil, Vineet Gupta, Tomer Koren, Yoram Singer

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Robust Bi-Tempered Logistic Loss Based on Bregman Divergences.

Ehsan Amid, Manfred K. Warmuth, Rohan Anil, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Semi-Cyclic Stochastic Gradient Descent.

Hubert Eichner, Tomer Koren, Brendan McMahan, Nathan Srebro, Kunal Talwar

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Linear-Quadratic Regulators Efficiently with only √T Regret.

Alon Cohen, Tomer Koren, Yishay Mansour

Proceedings of the 36th International Conference on Machine Learning, 2019

Better Algorithms for Stochastic Bandits with Adversarial Corruptions.

Anupam Gupta, Tomer Koren, Kunal Talwar

Proceedings of the Conference on Learning Theory, 2019

2018

Online Linear Quadratic Control.

Alon Cohen, Avinatan Hassidim, Tomer Koren, Nevena Lazic, Yishay Mansour, Kunal Talwar

Proceedings of the 35th International Conference on Machine Learning, 2018

Shampoo: Preconditioned Stochastic Tensor Optimization.

Vineet Gupta, Tomer Koren, Yoram Singer

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Chasing Ghosts: Competing with Stateful Policies.

Uriel Feige, Tomer Koren, Moshe Tennenholtz

SIAM J. Comput., 2017

A Unified Approach to Adaptive Regularization in Online and Stochastic Optimization.

Vineet Gupta, Tomer Koren, Yoram Singer

CoRR, 2017

Multi-Armed Bandits with Metric Movement Costs.

Tomer Koren, Roi Livni, Yishay Mansour

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Affine-Invariant Online Optimization and the Low-rank Experts Problem.

Tomer Koren, Roi Livni

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Bandits with Movement Costs and Adaptive Pricing.

Tomer Koren, Roi Livni, Yishay Mansour

Proceedings of the 30th Conference on Learning Theory, 2017

Tight Bounds for Bandit Combinatorial Optimization.

Alon Cohen, Tamir Hazan, Tomer Koren

Proceedings of the 30th Conference on Learning Theory, 2017

2016

A linear-time algorithm for trust region problems.

Elad Hazan, Tomer Koren

Math. Program., 2016

The computational power of optimization in online learning.

Elad Hazan, Tomer Koren

Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Online Pricing with Strategic and Patient Buyers.

Michal Feldman, Tomer Koren, Roi Livni, Yishay Mansour, Aviv Zohar

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.

Brian Bullins, Elad Hazan, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Online Learning with Feedback Graphs Without the Graphs.

Alon Cohen, Tamir Hazan, Tomer Koren

Proceedings of the 33nd International Conference on Machine Learning, 2016

Online Learning with Low Rank Experts.

Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour

Proceedings of the 29th Conference on Learning Theory, 2016

2015

Oracle-Based Robust Optimization via Online Learning.

Aharon Ben-Tal, Elad Hazan, Tomer Koren, Shie Mannor

Oper. Res., 2015

Fast Rates for Exp-concave Empirical Risk Minimization.

Tomer Koren, Kfir Y. Levy

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

Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff.

Ofer Dekel, Ronen Eldan, Tomer Koren

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

Bandit Convex Optimization: \(\sqrt{T}\) Regret in One Dimension.

Sébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres

Proceedings of The 28th Conference on Learning Theory, 2015

Online Learning with Feedback Graphs: Beyond Bandits.

Noga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren

Proceedings of The 28th Conference on Learning Theory, 2015

2014

Bandits with switching costs: <i>T</i>^2/3 regret.

Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres

Proceedings of the Symposium on Theory of Computing, 2014

The Blinded Bandit: Learning with Adaptive Feedback.

Ofer Dekel, Elad Hazan, Tomer Koren

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Logistic Regression: Tight Bounds for Stochastic and Online Optimization.

Elad Hazan, Tomer Koren, Kfir Y. Levy

Proceedings of The 27th Conference on Learning Theory, 2014

Online Learning with Composite Loss Functions.

Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres

Proceedings of The 27th Conference on Learning Theory, 2014

2013

Bandits with Switching Costs: T^{2/3} Regret.

Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres

CoRR, 2013

Distributed Exploration in Multi-Armed Bandits.

Eshcar Hillel, Zohar Shay Karnin, Tomer Koren, Ronny Lempel, Oren Somekh

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Almost Optimal Exploration in Multi-Armed Bandits.

Zohar Shay Karnin, Tomer Koren, Oren Somekh

Proceedings of the 30th International Conference on Machine Learning, 2013

Open Problem: Fast Stochastic Exp-Concave Optimization.

Tomer Koren

Proceedings of the COLT 2013, 2013

2012

Linear Regression with Limited Observation.

Elad Hazan, Tomer Koren

Proceedings of the 29th International Conference on Machine Learning, 2012

Supervised system identification based on local PCA models.

Tomer Koren, Ronen Talmon, Israel Cohen

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Optimal Algorithms for Ridge and Lasso Regression with Partially Observed Attributes

Elad Hazan, Tomer Koren

CoRR, 2011

Beating SGD: Learning SVMs in Sublinear Time.

Elad Hazan, Tomer Koren, Nati Srebro

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