A Simple Geometric Interpretation of SVM using Stochastic Adversaries. - Roi Livni; Koby Crammer; Amir Globerson (AISTATS, 2012)

Honest Compressions and Their Application to Compression Schemes. - Roi Livni; Pierre Simon (COLT, 2013)

Vanishing Component Analysis. - Roi Livni; David Lehavi; Sagi Schein; Hila Nachlieli; Shai Shalev-Shwartz; Amir Globerson (ICML (1), 2013)

A Provably Efficient Algorithm for Training Deep Networks - Roi Livni; Shai Shalev-Shwartz; Ohad Shamir (CoRR, 2013)

On the Computational Efficiency of Training Neural Networks. - Roi Livni; Shai Shalev-Shwartz; Ohad Shamir (NIPS, 2014)

Classification with Low Rank and Missing Data. - Elad Hazan; Roi Livni; Yishay Mansour (ICML, 2015)

Improper Deep Kernels. - Uri Heinemann; Roi Livni; Elad Eban; Gal Elidan; Amir Globerson (AISTATS, 2016)

Online Learning with Low Rank Experts. - Elad Hazan; Tomer Koren; Roi Livni; Yishay Mansour (COLT, 2016)

Online Pricing with Strategic and Patient Buyers. - Michal Feldman; Tomer Koren; Roi Livni; Yishay Mansour; Aviv Zohar (NIPS, 2016)

Learning Infinite-Layer Networks: Beyond the Kernel Trick. - Amir Globerson; Roi Livni (CoRR, 2016)

Representation learning theory (שער נוסף בעברית: תורת למידת הייצוג‏). - Roi Livni (2016)

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

Bandits with Movement Costs and Adaptive Pricing. - Tomer Koren; Roi Livni; Yishay Mansour (COLT, 2017)

Learning Infinite Layer Networks Without the Kernel Trick. - Roi Livni; Daniel Carmon; Amir Globerson (ICML, 2017)

Affine-Invariant Online Optimization and the Low-rank Experts Problem. - Tomer Koren; Roi Livni (NIPS, 2017)

Multi-Armed Bandits with Metric Movement Costs. - Tomer Koren; Roi Livni; Yishay Mansour (NIPS, 2017)

Learning by Refuting. - Pravesh K. Kothari; Roi Livni (CoRR, 2017)

On Communication Complexity of Classification Problems. - Daniel M. Kane; Roi Livni; Shay Moran; Amir Yehudayoff (Electron. Colloquium Comput. Complex., 2017)

Open problem: Improper learning of mixtures of Gaussians. - Elad Hazan; Roi Livni (COLT, 2018)

Improper Learning by Refuting. - Pravesh K. Kothari; Roi Livni (ITCS, 2018)

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

Graph-based Discriminators: Sample Complexity and Expressiveness. - Roi Livni; Yishay Mansour (NeurIPS, 2019)

Private PAC learning implies finite Littlestone dimension. - Noga Alon; Roi Livni; Maryanthe Malliaris; Shay Moran (STOC, 2019)

Passing Tests without Memorizing: Two Models for Fooling Discriminators. - Olivier Bousquet; Roi Livni; Shay Moran (CoRR, 2019)

On the Expressive Power of Kernel Methods and the Efficiency of Kernel Learning by Association Schemes. - Pravesh K. Kothari; Roi Livni (ALT, 2020)

An Equivalence Between Private Classification and Online Prediction. - Mark Bun; Roi Livni; Shay Moran (FOCS, 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 (NeurIPS, 2020)

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

A Limitation of the PAC-Bayes Framework. - Roi Livni; Shay Moran (NeurIPS, 2020)

SGD Generalizes Better Than GD (And Regularization Doesn't Help). - Idan Amir; 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)

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

Littlestone Classes are Privately Online Learnable. - Noah Golowich; Roi Livni (NeurIPS, 2021)

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, 2022)

Benign Underfitting of Stochastic Gradient Descent. - Tomer Koren; Roi Livni; Yishay Mansour; Uri Sherman (NeurIPS, 2022)

Private and Online Learnability Are Equivalent. - Noga Alon; Mark Bun; Roi Livni; Maryanthe Malliaris; Shay Moran (J. ACM, 2022)

Information Theoretic Lower Bounds for Information Theoretic Upper Bounds. - Roi Livni (NeurIPS, 2023)

The sample complexity of ERMs in stochastic convex optimization. - Daniel Carmon; Amir Yehudayoff; Roi Livni (AISTATS, 2024)

Can Copyright Be Reduced to Privacy? - Niva Elkin-Koren; Uri Hacohen; Roi Livni; Shay Moran (FORC, 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 001 (ICML, 2024)

Making Progress Based on False Discoveries. - Roi Livni (ITCS, 2024)

The Sample Complexity of Gradient Descent in Stochastic Convex Optimization. - Roi Livni (NeurIPS, 2024)

Credit Attribution and Stable Compression. - Roi Livni; Shay Moran; Kobbi Nissim; Chirag Pabbaraju (NeurIPS, 2024)

Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization. - Idan Attias; Gintare Karolina Dziugaite; Mahdi Haghifam; Roi Livni; Daniel M. Roy 001 (CoRR, 2024)

Not All Similarities Are Created Equal: Leveraging Data-Driven Biases to Inform GenAI Copyright Disputes. - Uri Hacohen; Adi Haviv; Shahar Sarfaty; Bruria Friedman; Niva Elkin-Koren; Roi Livni; Amit H. Bermano (CoRR, 2024)

Not Every Image is Worth a Thousand Words: Quantifying Originality in Stable Diffusion. - Adi Haviv; Shahar Sarfaty; Uri Hacohen; Niva Elkin-Koren; Roi Livni; Amit H. Bermano (CoRR, 2024)

On the Dichotomy Between Privacy and Traceability in ℓp Stochastic Convex Optimization. - Sasha Voitovych; Mahdi Haghifam; Idan Attias; Gintare Karolina Dziugaite; Roi Livni; Daniel M. Roy 001 (CoRR, 2025)

Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization. - Shira Vansover-Hager; Tomer Koren; Roi Livni (CoRR, 2025)

Low Resource Reconstruction Attacks Through Benign Prompts. - Sol Yarkoni; Roi Livni (CoRR, 2025)