| 2026 | COLT | Statistical Learning from Attribution Sets. | Lorne Applebaum, Rbert Busa-Fekete, August Y. Chen, Claudio Gentile, Tomer Koren, Aryan Mokhtari |
| 2026 | COLT | The Sample Complexity of Multiclass and Sparse Contextual Bandits. | Liad Erez, Fan Chen, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran, Alexander Rakhlin |
| 2026 | COLT | The Hidden Cost of Approximation in Online Mirror Descent. | Ofir Schlisselberg, Uri Sherman, Tomer Koren, Yishay Mansour |
| 2026 | STOC | Sample Complexity of Agnostic Multiclass Classification: Natarajan Dimension Strikes Back. | Alon Cohen, Liad Erez, Steve Hanneke, Tomer Koren, Yishay Mansour, Shay Moran, Qian Zhang |
| 2025 | AISTATS | Locally Optimal Descent for Dynamic Stepsize Scheduling. | Gilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain |
| 2025 | ALT | The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization. | Matan Schliserman, Uri Sherman, Tomer Koren |
| 2025 | ICML | Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching. | Amit Attia, Ofir Gaash, Tomer Koren |
| 2025 | ICML | Nearly Optimal Sample Complexity for Learning with Label Proportions. | Rbert Istvan Busa-Fekete, Travis Dick, Claudio Gentile, Haim Kaplan, Tomer Koren, Uri Stemmer |
| 2025 | ICML | Dueling Convex Optimization with General Preferences. | Aadirupa Saha, Tomer Koren, Yishay Mansour |
| 2025 | ICML | Convergence of Policy Mirror Descent Beyond Compatible Function Approximation. | Uri Sherman, Tomer Koren, Yishay Mansour |
| 2025 | ICML | Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization. | Shira Vansover-Hager, Tomer Koren, Roi Livni |
| 2024 | AISTATS | Faster Convergence with MultiWay Preferences. | Aadirupa Saha, Vitaly Feldman, Yishay Mansour, Tomer Koren |
| 2024 | COLT | The Real Price of Bandit Information in Multiclass Classification. | Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran |
| 2024 | ICML | How Free is Parameter-Free Stochastic Optimization? | Amit Attia, Tomer Koren |
| 2024 | ICML | Rate-Optimal Policy Optimization for Linear Markov Decision Processes. | Uri Sherman, Alon Cohen, Tomer Koren, Yishay Mansour |
| 2023 | COLT | Private Online Prediction from Experts: Separations and Faster Rates. | Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2023 | ICML | Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. | Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2023 | ICML | SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance. | Amit Attia, Tomer Koren |
| 2023 | ICML | Regret Minimization and Convergence to Equilibria in General-sum Markov Games. | Liad Erez, Tal Lancewicki, Uri Sherman, Tomer Koren, Yishay Mansour |
| 2023 | ICML | Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation. | Uri Sherman, Tomer Koren, Yishay Mansour |
| 2022 | COLT | Uniform Stability for First-Order Empirical Risk Minimization. | Amit Attia, Tomer Koren |
| 2022 | COLT | Efficient Online Linear Control with Stochastic Convex Costs and Unknown Dynamics. | Asaf B. Cassel, Alon Cohen, Tomer Koren |
| 2022 | COLT | Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond. | Matan Schliserman, Tomer Koren |
| 2021 | COLT | SGD Generalizes Better Than GD (And Regularization Doesn't Help). | Idan Amir, Tomer Koren, Roi Livni |
| 2021 | COLT | Online Markov Decision Processes with Aggregate Bandit Feedback. | Alon Cohen, Haim Kaplan, Tomer Koren, Yishay Mansour |
| 2021 | COLT | Lazy OCO: Online Convex Optimization on a Switching Budget. | Uri Sherman, Tomer Koren |
| 2021 | ICML | Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry. | Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2021 | ICML | Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with √T Regret. | Asaf B. Cassel, Tomer Koren |
| 2021 | ICML | Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions. | Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour |
| 2021 | ICML | Adversarial Dueling Bandits. | Aadirupa Saha, Tomer Koren, Yishay Mansour |
| 2021 | ICML | Dueling Convex Optimization. | Aadirupa Saha, Tomer Koren, Yishay Mansour |
| 2020 | COLT | Open Problem: Tight Convergence of SGD in Constant Dimension. | Tomer Koren, Shahar Segal |
| 2020 | ICML | Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently. | Asaf B. Cassel, Alon Cohen, Tomer Koren |
| 2020 | STOC | Private stochastic convex optimization: optimal rates in linear time. | Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2019 | COLT | Better Algorithms for Stochastic Bandits with Adversarial Corruptions. | Anupam Gupta, Tomer Koren, Kunal Talwar |
| 2019 | ICML | Learning Linear-Quadratic Regulators Efficiently with only √T Regret. | Alon Cohen, Tomer Koren, Yishay Mansour |
| 2019 | ICML | Semi-Cyclic Stochastic Gradient Descent. | Hubert Eichner, Tomer Koren, Brendan McMahan, Nathan Srebro, Kunal Talwar |
| 2018 | ICML | Shampoo: Preconditioned Stochastic Tensor Optimization. | Vineet Gupta, Tomer Koren, Yoram Singer |
| 2018 | ICML | Online Linear Quadratic Control. | Alon Cohen, Avinatan Hassidim, Tomer Koren, Nevena Lazic, Yishay Mansour, Kunal Talwar |
| 2017 | COLT | Tight Bounds for Bandit Combinatorial Optimization. | Alon Cohen, Tamir Hazan, Tomer Koren |
| 2017 | COLT | Bandits with Movement Costs and Adaptive Pricing. | Tomer Koren, Roi Livni, Yishay Mansour |
| 2016 | COLT | Online Learning with Low Rank Experts. | Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour |
| 2016 | ICML | Online Learning with Feedback Graphs Without the Graphs. | Alon Cohen, Tamir Hazan, Tomer Koren |
| 2016 | STOC | The computational power of optimization in online learning. | Elad Hazan, Tomer Koren |
| 2015 | COLT | Online Learning with Feedback Graphs: Beyond Bandits. | Noga Alon, Nicol Cesa-Bianchi, Ofer Dekel, Tomer Koren |
| 2015 | COLT | Bandit Convex Optimization: \(\sqrt{T}\) Regret in One Dimension. | Sbastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres |
| 2014 | COLT | Online Learning with Composite Loss Functions. | Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres |
| 2014 | COLT | Logistic Regression: Tight Bounds for Stochastic and Online Optimization. | Elad Hazan, Tomer Koren, Kfir Y. Levy |
| 2014 | FOCS | Chasing Ghosts: Competing with Stateful Policies. | Uriel Feige, Tomer Koren, Moshe Tennenholtz |
| 2014 | STOC | Bandits with switching costs: | Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres |
| 2013 | COLT | Open Problem: Fast Stochastic Exp-Concave Optimization. | Tomer Koren |
| 2013 | ICML | Almost Optimal Exploration in Multi-Armed Bandits. | Zohar Shay Karnin, Tomer Koren, Oren Somekh |
| 2012 | ICASSP | Supervised system identification based on local PCA models. | Tomer Koren, Ronen Talmon, Israel Cohen |
| 2012 | ICML | Linear Regression with Limited Observation. | Elad Hazan, Tomer Koren |