Roi Livni - RankMe

83 papers A* 27A 5B 2Journal 42Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	All ERMs Can Fail in Stochastic Convex Optimization Lower Bounds in Linear Dimension. CoRR Tal Burla, Roi Livni
2026	J	`jnl`	Margin in Abstract Spaces. CoRR Yair Ashlagi, Roi Livni, Shay Moran, Tom Waknine
2026	J	`jnl`	We Should Separate Memorization from Copyright. CoRR Adi Haviv, Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran
2025	J	`jnl`	CARLoS: Retrieval via Concise Assessment Representation of LoRAs at Scale. CoRR Shahar Sarfaty, Adi Haviv, Uri Hacohen, Niva Elkin-Koren, Roi Livni, Amit H. Bermano
2025	J	`jnl`	Low Resource Reconstruction Attacks Through Benign Prompts. CoRR Sol Yarkoni, Roi Livni
2025	J	`jnl`	On the Dichotomy Between Privacy and Traceability in ℓ CoRR Sasha Voitovych, Mahdi Haghifam, Idan Attias, Gintare Karolina Dziugaite, Roi Livni, Daniel M. Roy
2025	A*	`conf`	Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization. ICML Shira Vansover-Hager, Tomer Koren, Roi Livni
2025	J	`jnl`	Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization. CoRR Shira Vansover-Hager, Tomer Koren, Roi Livni
2024	—	`conf`	Can Copyright Be Reduced to Privacy? FORC Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran
2024	A*	`conf`	Credit Attribution and Stable Compression. NeurIPS Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju
2024	J	`jnl`	Credit Attribution and Stable Compression. CoRR Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju
2024	J	`jnl`	Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization. CoRR Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy
2024	A*	`conf`	Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing. ICML Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy
2024	A	`conf`	Making Progress Based on False Discoveries. ITCS Roi Livni
2024	J	`jnl`	Not All Similarities Are Created Equal: Leveraging Data-Driven Biases to Inform GenAI Copyright Disputes. CoRR Uri Hacohen, Adi Haviv, Shahar Sarfaty, Bruria Friedman, Niva Elkin-Koren, Roi Livni, Amit H. Bermano
2024	J	`jnl`	Not Every Image is Worth a Thousand Words: Quantifying Originality in Stable Diffusion. CoRR Adi Haviv, Shahar Sarfaty, Uri Hacohen, Niva Elkin-Koren, Roi Livni, Amit H. Bermano
2024	A*	`conf`	The Sample Complexity of Gradient Descent in Stochastic Convex Optimization. NeurIPS Roi Livni
2024	J	`jnl`	The Sample Complexity of Gradient Descent in Stochastic Convex Optimization. CoRR Roi Livni
2024	A	`conf`	The sample complexity of ERMs in stochastic convex optimization. AISTATS Daniel Carmon, Amir Yehudayoff, Roi Livni
2023	J	`jnl`	Can Copyright be Reduced to Privacy? CoRR Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran
2023	A*	`conf`	Information Theoretic Lower Bounds for Information Theoretic Upper Bounds. NeurIPS Roi Livni
2023	J	`jnl`	Information Theoretic Lower Bounds for Information Theoretic Upper Bounds. CoRR Roi Livni
2023	J	`jnl`	The Sample Complexity Of ERMs In Stochastic Convex Optimization. CoRR Daniel Carmon, Roi Livni, Amir Yehudayoff
2022	A*	`conf`	Benign Underfitting of Stochastic Gradient Descent. NeurIPS Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman
2022	J	`jnl`	Benign Underfitting of Stochastic Gradient Descent. CoRR Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman
2022	A*	`conf`	Better Best of Both Worlds Bounds for Bandits with Switching Costs. NeurIPS Idan Amir, Guy Azov, Tomer Koren, Roi Livni
2022	J	`jnl`	Better Best of Both Worlds Bounds for Bandits with Switching Costs. CoRR Idan Amir, Guy Azov, Tomer Koren, Roi Livni
2022	J	`jnl`	Making Progress Based on False Discoveries. CoRR Roi Livni
2022	J	`jnl`	Private and Online Learnability Are Equivalent. J. ACM Noga Alon, Mark Bun, Roi Livni, Maryanthe Malliaris, Shay Moran
2022	A*	`conf`	Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization. NeurIPS Idan Amir, Roi Livni, Nati Srebro
2022	J	`jnl`	Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization. CoRR Idan Amir, Roi Livni, Nathan Srebro
2021	A*	`conf`	Littlestone Classes are Privately Online Learnable. NeurIPS Noah Golowich, Roi Livni
2021	J	`jnl`	Littlestone Classes are Privately Online Learnable. CoRR Noah Golowich, Roi Livni
2021	A*	`conf`	Never Go Full Batch (in Stochastic Convex Optimization). NeurIPS Idan Amir, Yair Carmon, Tomer Koren, Roi Livni
2021	J	`jnl`	Never Go Full Batch (in Stochastic Convex Optimization). CoRR Idan Amir, Yair Carmon, Tomer Koren, Roi Livni
2021	A*	`conf`	Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games. COLT Steve Hanneke, Roi Livni, Shay Moran
2021	J	`jnl`	Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games. CoRR Steve Hanneke, Roi Livni, Shay Moran
2021	A*	`conf`	SGD Generalizes Better Than GD (And Regularization Doesn't Help). COLT Idan Amir, Tomer Koren, Roi Livni
2021	J	`jnl`	SGD Generalizes Better Than GD (And Regularization Doesn't Help). CoRR Idan Amir, Tomer Koren, Roi Livni
2020	A*	`conf`	A Limitation of the PAC-Bayes Framework. NeurIPS Roi Livni, Shay Moran
2020	J	`jnl`	A Limitation of the PAC-Bayes Framework. CoRR Roi Livni, Shay Moran
2020	A*	`conf`	An Equivalence Between Private Classification and Online Prediction. FOCS Mark Bun, Roi Livni, Shay Moran
2020	J	`jnl`	An Equivalence Between Private Classification and Online Prediction. CoRR Mark Bun, Roi Livni, Shay Moran
2020	A*	`conf`	Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study. NeurIPS Assaf Dauber, Meir Feder, Tomer Koren, Roi Livni
2020	J	`jnl`	Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study. CoRR Assaf Dauber, Meir Feder, Tomer Koren, Roi Livni
2020	B	`conf`	On the Expressive Power of Kernel Methods and the Efficiency of Kernel Learning by Association Schemes. ALT Pravesh K. Kothari, Roi Livni
2020	A*	`conf`	Prediction with Corrupted Expert Advice. NeurIPS Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni
2020	J	`jnl`	Prediction with Corrupted Expert Advice. CoRR Idan Amir, Idan Attias, Tomer Koren, Roi Livni, Yishay Mansour
2020	A*	`conf`	Synthetic Data Generators - Sequential and Private. NeurIPS Olivier Bousquet, Roi Livni, Shay Moran
2019	B	`conf`	Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning. ALT Brian Bullins, Elad Hazan, Adam Kalai, Roi Livni
2019	A*	`conf`	Graph-based Discriminators: Sample Complexity and Expressiveness. NeurIPS Roi Livni, Yishay Mansour
2019	J	`jnl`	Graph-based Discriminators: Sample Complexity and Expressiveness. CoRR Roi Livni, Yishay Mansour
2019	A*	`conf`	On Communication Complexity of Classification Problems. COLT Daniel Kane, Roi Livni, Shay Moran, Amir Yehudayoff
2019	J	`jnl`	On the Expressive Power of Kernel Methods and the Efficiency of Kernel Learning by Association Schemes. CoRR Pravesh K. Kothari, Roi Livni
2019	J	`jnl`	Passing Tests without Memorizing: Two Models for Fooling Discriminators. CoRR Olivier Bousquet, Roi Livni, Shay Moran
2019	A*	`conf`	Private PAC learning implies finite Littlestone dimension. STOC Noga Alon, Roi Livni, Maryanthe Malliaris, Shay Moran
2018	A	`conf`	Improper Learning by Refuting. ITCS Pravesh K. Kothari, Roi Livni
2018	A*	`conf`	Open problem: Improper learning of mixtures of Gaussians. COLT Elad Hazan, Roi Livni
2018	J	`jnl`	Private PAC learning implies finite Littlestone dimension. CoRR Noga Alon, Roi Livni, Maryanthe Malliaris, Shay Moran
2017	—	`conf`	Affine-Invariant Online Optimization and the Low-rank Experts Problem. NIPS Tomer Koren, Roi Livni
2017	A*	`conf`	Bandits with Movement Costs and Adaptive Pricing. COLT Tomer Koren, Roi Livni, Yishay Mansour
2017	J	`jnl`	Bandits with Movement Costs and Adaptive Pricing. CoRR Tomer Koren, Roi Livni, Yishay Mansour
2017	A*	`conf`	Effective Semisupervised Learning on Manifolds. COLT Amir Globerson, Roi Livni, Shai Shalev-Shwartz
2017	A*	`conf`	Learning Infinite Layer Networks Without the Kernel Trick. ICML Roi Livni, Daniel Carmon, Amir Globerson
2017	J	`jnl`	Learning by Refuting. CoRR Pravesh K. Kothari, Roi Livni
2017	—	`conf`	Multi-Armed Bandits with Metric Movement Costs. NIPS Tomer Koren, Roi Livni, Yishay Mansour
2017	J	`jnl`	Multi-Armed Bandits with Metric Movement Costs. CoRR Tomer Koren, Roi Livni, Yishay Mansour
2017	J	`jnl`	On Communication Complexity of Classification Problems. CoRR Daniel M. Kane, Roi Livni, Shay Moran, Amir Yehudayoff
2017	J	`jnl`	On Communication Complexity of Classification Problems. Electron. Colloquium Comput. Complex. Daniel M. Kane, Roi Livni, Shay Moran, Amir Yehudayoff
2016	A	`conf`	Improper Deep Kernels. AISTATS Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson
2016	J	`jnl`	Learning Infinite-Layer Networks: Beyond the Kernel Trick. CoRR Amir Globerson, Roi Livni
2016	A*	`conf`	Online Learning with Low Rank Experts. COLT Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour
2016	J	`jnl`	Online Learning with Low Rank Experts. CoRR Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour
2016	—	`conf`	Online Pricing with Strategic and Patient Buyers. NIPS Michal Feldman, Tomer Koren, Roi Livni, Yishay Mansour, Aviv Zohar
2016	—	`—`	Representation learning theory (שער נוסף בעברית: תורת למידת הייצוג‏). Roi Livni
2015	A*	`conf`	Classification with Low Rank and Missing Data. ICML Elad Hazan, Roi Livni, Yishay Mansour
2015	J	`jnl`	Classification with Low Rank and Missing Data. CoRR Elad Hazan, Roi Livni, Yishay Mansour
2014	—	`conf`	On the Computational Efficiency of Training Neural Networks. NIPS Roi Livni, Shai Shalev-Shwartz, Ohad Shamir
2014	J	`jnl`	On the Computational Efficiency of Training Neural Networks. CoRR Roi Livni, Shai Shalev-Shwartz, Ohad Shamir
2013	J	`jnl`	A Provably Efficient Algorithm for Training Deep Networks CoRR Roi Livni, Shai Shalev-Shwartz, Ohad Shamir
2013	A*	`conf`	Honest Compressions and Their Application to Compression Schemes. COLT Roi Livni, Pierre Simon
2013	—	`conf`	Vanishing Component Analysis. ICML (1) Roi Livni, David Lehavi, Sagi Schein, Hila Nachlieli, Shai Shalev-Shwartz, Amir Globerson
2012	A	`conf`	A Simple Geometric Interpretation of SVM using Stochastic Adversaries. AISTATS Roi Livni, Koby Crammer, Amir Globerson