Livni, Roi

36 publications

NeurIPS 2025 On Traceability in $\ell_p$ Stochastic Convex Optimization Sasha Voitovych, Mahdi Haghifam, Idan Attias, Gintare Karolina Dziugaite, Roi Livni, Daniel M. Roy

ICML 2025 Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization Shira Vansover-Hager, Tomer Koren, Roi Livni

NeurIPS 2024 Credit Attribution and Stable Compression Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju

ICML 2024 Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy

AISTATS 2024 The Sample Complexity of ERMs in Stochastic Convex Optimization Daniel Carmon, Amir Yehudayoff, Roi Livni

NeurIPS 2024 The Sample Complexity of Gradient Descent in Stochastic Convex Optimization Roi Livni, Amir, Koren, Livni, Schliserman, Sherman, Koren, Shalev-Shwartz, Shamir, Srebro, Sridharan

NeurIPSW 2023 Can Copyright Be Reduced to Privacy Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran

NeurIPS 2023 Information Theoretic Lower Bounds for Information Theoretic Upper Bounds Roi Livni

NeurIPS 2022 Benign Underfitting of Stochastic Gradient Descent Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman

NeurIPS 2022 Better Best of Both Worlds Bounds for Bandits with Switching Costs Idan Amir, Guy Azov, Tomer Koren, Roi Livni

NeurIPS 2022 Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization Idan Amir, Roi Livni, Nati Srebro

NeurIPS 2021 Littlestone Classes Are Privately Online Learnable Noah Golowich, Roi Livni

NeurIPS 2021 Never Go Full Batch (in Stochastic Convex Optimization) Idan Amir, Yair Carmon, Tomer Koren, Roi Livni

COLT 2021 Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games Steve Hanneke, Roi Livni, Shay Moran

COLT 2021 SGD Generalizes Better than GD (And Regularization Doesn’t Help) Idan Amir, Tomer Koren, Roi Livni

NeurIPS 2020 A Limitation of the PAC-Bayes Framework Roi Livni, Shay Moran

NeurIPS 2020 Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study Assaf Dauber, Meir Feder, Tomer Koren, Roi Livni

NeurIPS 2020 Prediction with Corrupted Expert Advice Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni

NeurIPS 2020 Synthetic Data Generators -- Sequential and Private Olivier Bousquet, Roi Livni, Shay Moran

ALT 2019 Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning Brian Bullins, Elad Hazan, Adam Kalai, Roi Livni

NeurIPS 2019 Graph-Based Discriminators: Sample Complexity and Expressiveness Roi Livni, Yishay Mansour

COLT 2019 On Communication Complexity of Classification Problems Daniel Kane, Roi Livni, Shay Moran, Amir Yehudayoff

COLT 2018 Open Problem: Improper Learning of Mixtures of Gaussians Elad Hazan, Roi Livni

NeurIPS 2017 Affine-Invariant Online Optimization and the Low-Rank Experts Problem Tomer Koren, Roi Livni

COLT 2017 Bandits with Movement Costs and Adaptive Pricing Tomer Koren, Roi Livni, Yishay Mansour

COLT 2017 Effective Semisupervised Learning on Manifolds Amir Globerson, Roi Livni, Shai Shalev-Shwartz

ICML 2017 Learning Infinite Layer Networks Without the Kernel Trick Roi Livni, Daniel Carmon, Amir Globerson

NeurIPS 2017 Multi-Armed Bandits with Metric Movement Costs Tomer Koren, Roi Livni, Yishay Mansour

AISTATS 2016 Improper Deep Kernels Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson

COLT 2016 Online Learning with Low Rank Experts Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour

NeurIPS 2016 Online Pricing with Strategic and Patient Buyers Michal Feldman, Tomer Koren, Roi Livni, Yishay Mansour, Aviv Zohar

ICML 2015 Classification with Low Rank and Missing Data Elad Hazan, Roi Livni, Yishay Mansour

NeurIPS 2014 On the Computational Efficiency of Training Neural Networks Roi Livni, Shai Shalev-Shwartz, Ohad Shamir

COLT 2013 Honest Compressions and Their Application to Compression Schemes Roi Livni, Pierre Simon

ICML 2013 Vanishing Component Analysis Roi Livni, David Lehavi, Sagi Schein, Hila Nachliely, Shai Shalev-Shwartz, Amir Globerson

AISTATS 2012 A Simple Geometric Interpretation of SVM Using Stochastic Adversaries Roi Livni, Koby Crammer, Amir Globerson