Kfir Y. Levy - RankMe

69 papers A* 18A 2Journal 41Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning. CoRR Ze'ev Zukerman, Bassel Hamoud, Kfir Y. Levy
2025	J	`jnl`	DE-PADA: Personalized Augmentation and Domain Adaptation for ECG Biometrics Across Physiological States. CoRR Amro Abu Saleh, Elliot Sprecher, Kfir Y. Levy, Daniel H. Lange
2025	J	`jnl`	Enhancing Parallelism in Decentralized Stochastic Convex Optimization. CoRR Ofri Eisen, Ron Dorfman, Kfir Y. Levy
2025	J	`jnl`	Prediction-Powered Semi-Supervised Learning with Online Power Tuning. CoRR Noa Shoham, Ron Dorfman, Shalev Shaer, Kfir Y. Levy, Yaniv Romano
2025	J	`jnl`	Safety in the Face of Adversity: Achieving Zero Constraint Violation in Online Learning with Slowly Changing Constraints. CoRR Bassel Hamoud, Ilnura Usmanova, Kfir Y. Levy
2025	J	`jnl`	Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML. CoRR Tehila Dahan, Kfir Y. Levy
2024	J	`jnl`	Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers. CoRR Ron Dorfman, Naseem Yehya, Kfir Y. Levy
2024	J	`jnl`	Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training. CoRR Tehila Dahan, Kfir Y. Levy
2024	J	`jnl`	No-regret dynamics in the Fenchel game: a unified framework for algorithmic convex optimization. Math. Program. Jun-Kun Wang, Jacob D. Abernethy, Kfir Y. Levy
2024	J	`jnl`	On the Global Convergence of Policy Gradient in Average Reward Markov Decision Processes. CoRR Navdeep Kumar, Yashaswini Murthy, Itai Shufaro, Kfir Y. Levy, R. Srikant, Shie Mannor
2024	J	`jnl`	Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems. CoRR Roie Reshef, Kfir Y. Levy
2024	A*	`conf`	SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization. NeurIPS Tehila Dahan, Kfir Y. Levy
2024	A*	`conf`	Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML. NeurIPS Tehila Dahan, Kfir Y. Levy
2023	J	`jnl`	DoCoFL: Downlink Compression for Cross-Device Federated Learning. CoRR Ron Dorfman, Shay Vargaftik, Yaniv Ben-Itzhak, Kfir Y. Levy
2023	A*	`conf`	DropCompute: simple and more robust distributed synchronous training via compute variance reduction. NeurIPS Niv Giladi, Shahar Gottlieb, Moran Shkolnik, Asaf Karnieli, Ron Banner, Elad Hoffer, Kfir Y. Levy, Daniel Soudry
2023	A*	`conf`	Meta-Learning Adversarial Bandit Algorithms. NeurIPS Misha Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Zhiwei Steven Wu
2023	J	`jnl`	Meta-Learning Adversarial Bandit Algorithms. CoRR Mikhail Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Zhiwei Steven Wu
2023	A*	`conf`	Policy Gradient for Rectangular Robust Markov Decision Processes. NeurIPS Navdeep Kumar, Esther Derman, Matthieu Geist, Kfir Y. Levy, Shie Mannor
2023	A	`conf`	Robust Linear Regression for General Feature Distribution. AISTATS Tom Norman, Nir Weinberger, Kfir Y. Levy
2023	J	`jnl`	SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization. CoRR Kfir Y. Levy
2023	J	`jnl`	μ CoRR Kfir Y. Levy
2022	J	`jnl`	Adapting to Mixing Time in Stochastic Optimization with Markovian Data. CoRR Ron Dorfman, Kfir Y. Levy
2022	J	`jnl`	Online Meta-Learning in Adversarial Multi-Armed Bandits. CoRR Ilya Osadchiy, Kfir Y. Levy, Ron Meir
2022	J	`jnl`	Robust Linear Regression for General Feature Distribution. CoRR Tom Norman, Nir Weinberger, Kfir Y. Levy
2022	A*	`conf`	UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees. ICML Kimon Antonakopoulos, Dong Quan Vu, Volkan Cevher, Kfir Y. Levy, Panayotis Mertikopoulos
2021	A*	`conf`	Fast Projection Onto Convex Smooth Constraints. ICML Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Y. Levy
2021	A*	`conf`	Faster Neural Network Training with Approximate Tensor Operations. NeurIPS Menachem Adelman, Kfir Y. Levy, Ido Hakimi, Mark Silberstein
2021	J	`jnl`	Generative Minimization Networks: Training GANs Without Competition. CoRR Paulina Grnarova, Yannic Kilcher, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann
2021	A*	`conf`	LAGA: Lagged AllReduce with Gradient Accumulation for Minimal Idle Time. ICDM Ido Hakimi, Rotem Zamir Aviv, Kfir Y. Levy, Assaf Schuster
2021	J	`jnl`	Learning Under Delayed Feedback: Implicitly Adapting to Gradient Delays. CoRR Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Y. Levy
2021	J	`jnl`	No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization. CoRR Jun-Kun Wang, Jacob D. Abernethy, Kfir Y. Levy
2021	J	`jnl`	STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization. CoRR Kfir Y. Levy, Ali Kavis, Volkan Cevher
2021	A*	`conf`	STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization. NeurIPS Kfir Y. Levy, Ali Kavis, Volkan Cevher
2020	A*	`conf`	Adaptive Sampling for Stochastic Risk-Averse Learning. NeurIPS Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause
2020	J	`jnl`	Multi-Player Bandits: The Adversarial Case. J. Mach. Learn. Res. Pragnya Alatur, Kfir Y. Levy, Andreas Krause
2020	A*	`conf`	Online Convex Optimization in the Random Order Model. ICML Dan Garber, Gal Korcia, Kfir Y. Levy
2019	A*	`conf`	A Domain Agnostic Measure for Monitoring and Evaluating GANs. NeurIPS Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Ian J. Goodfellow, Thomas Hofmann, Andreas Krause
2019	A*	`conf`	A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise. COLT Francis R. Bach, Kfir Y. Levy
2019	J	`jnl`	A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise. CoRR Francis R. Bach, Kfir Y. Levy
2019	—	`conf`	Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations. CDC Sebastian Curi, Kfir Y. Levy, Andreas Krause
2019	J	`jnl`	Adaptive Sampling for Stochastic Risk-Averse Learning. CoRR Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause
2019	J	`jnl`	Multi-Player Bandits: The Adversarial Case. CoRR Pragnya Alatur, Kfir Y. Levy, Andreas Krause
2019	J	`jnl`	Online Variance Reduction with Mixtures. CoRR Zalán Borsos, Sebastian Curi, Kfir Y. Levy, Andreas Krause
2019	A	`conf`	Projection Free Online Learning over Smooth Sets. AISTATS Kfir Y. Levy, Andreas Krause
2019	A*	`conf`	UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization. NeurIPS Ali Kavis, Kfir Y. Levy, Francis R. Bach, Volkan Cevher
2019	J	`jnl`	UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization. CoRR Ali Kavis, Kfir Y. Levy, Francis R. Bach, Volkan Cevher
2018	—	`conf`	An Online Learning Approach to Generative Adversarial Networks. ICLR (Poster) Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause
2018	J	`jnl`	Evaluating GANs via Duality. CoRR Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Thomas Hofmann, Andreas Krause
2018	A*	`conf`	Faster Rates for Convex-Concave Games. COLT Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang
2018	J	`jnl`	Faster Rates for Convex-Concave Games. CoRR Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang
2018	J	`jnl`	Online Adaptive Methods, Universality and Acceleration. CoRR Kfir Y. Levy, Alp Yurtsever, Volkan Cevher
2018	A*	`conf`	Online Variance Reduction for Stochastic Optimization. COLT Zalan Borsos, Andreas Krause, Kfir Y. Levy
2018	J	`jnl`	Online Variance Reduction for Stochastic Optimization. CoRR Zalán Borsos, Andreas Krause, Kfir Y. Levy
2018	J	`jnl`	Unsupervised Imitation Learning. CoRR Sebastian Curi, Kfir Y. Levy, Andreas Krause
2017	J	`jnl`	An Online Learning Approach to Generative Adversarial Networks. CoRR Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause
2017	J	`jnl`	Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. CoRR An Bian, Kfir Y. Levy, Andreas Krause, Joachim M. Buhmann
2017	—	`conf`	Online to Offline Conversions, Universality and Adaptive Minibatch Sizes. NIPS Kfir Y. Levy
2017	J	`jnl`	Online to Offline Conversions, Universality and Adaptive Minibatch Sizes. CoRR Kfir Y. Levy
2017	J	`jnl`	k*-Nearest Neighbors: From Global to Local. CoRR Oren Anava, Kfir Y. Levy
2016	J	`jnl`	The Power of Normalization: Faster Evasion of Saddle Points. CoRR Kfir Y. Levy
2016	—	`conf`	k*-Nearest Neighbors: From Global to Local. NIPS Oren Anava, Kfir Y. Levy
2015	—	`conf`	Beyond Convexity: Stochastic Quasi-Convex Optimization. NIPS Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz
2015	J	`jnl`	Beyond Convexity: Stochastic Quasi-Convex Optimization. CoRR Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz
2015	—	`conf`	Fast Rates for Exp-concave Empirical Risk Minimization. NIPS Tomer Koren, Kfir Y. Levy
2015	J	`jnl`	On Graduated Optimization for Stochastic Non-Convex Problems. CoRR Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz
2014	—	`conf`	Bandit Convex Optimization: Towards Tight Bounds. NIPS Elad Hazan, Kfir Y. Levy
2014	A*	`conf`	Logistic Regression: Tight Bounds for Stochastic and Online Optimization. COLT Elad Hazan, Tomer Koren, Kfir Y. Levy
2014	J	`jnl`	Logistic Regression: Tight Bounds for Stochastic and Online Optimization. CoRR Elad Hazan, Tomer Koren, Kfir Y. Levy
2011	—	`conf`	Unified Inter and Intra Options Learning Using Policy Gradient Methods. EWRL Kfir Y. Levy, Nahum Shimkin