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ORCIDKfir Y. Levy
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- affiliation: Technion, Haifa, Faculty of Industrial Engineering and Management
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2020 – today
- 2022
[i25]Tom Norman, Nir Weinberger, Kfir Y. Levy:
Robust Linear Regression for General Feature Distribution. CoRR abs/2202.02080 (2022)- [i24]Ron Dorfman, Kfir Y. Levy:
Adapting to Mixing Time in Stochastic Optimization with Markovian Data. CoRR abs/2202.04428 (2022) - [i23]Ali Kavis, Kfir Yehuda Levy, Volkan Cevher:
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize. CoRR abs/2204.02833 (2022) - 2021
- [c26]Ido Hakimi, Rotem Zamir Aviv, Kfir Y. Levy, Assaf Schuster:
LAGA: Lagged AllReduce with Gradient Accumulation for Minimal Idle Time. ICDM 2021: 171-180 - [c25]Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Yehuda Levy:
Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge. ICML 2021: 436-445 - [c24]Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Y. Levy:
Fast Projection Onto Convex Smooth Constraints. ICML 2021: 10476-10486 - [c23]Kfir Y. Levy, Ali Kavis, Volkan Cevher:
STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization. NeurIPS 2021: 20571-20582 - [c22]Menachem Adelman, Kfir Y. Levy, Ido Hakimi, Mark Silberstein:
Faster Neural Network Training with Approximate Tensor Operations. NeurIPS 2021: 27877-27889 - [i22]Paulina Grnarova, Yannic Kilcher, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann:
Generative Minimization Networks: Training GANs Without Competition. CoRR abs/2103.12685 (2021) - [i21]Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Y. Levy:
Learning Under Delayed Feedback: Implicitly Adapting to Gradient Delays. CoRR abs/2106.12261 (2021) - [i20]Kfir Y. Levy, Ali Kavis, Volkan Cevher:
STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization. CoRR abs/2111.01040 (2021) - [i19]Jun-Kun Wang, Jacob D. Abernethy, Kfir Y. Levy:
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization. CoRR abs/2111.11309 (2021) - 2020
- [j1]Pragnya Alatur, Kfir Y. Levy, Andreas Krause:
Multi-Player Bandits: The Adversarial Case. J. Mach. Learn. Res. 21: 77:1-77:23 (2020) - [c21]Dan Garber, Gal Korcia, Kfir Y. Levy:
Online Convex Optimization in the Random Order Model. ICML 2020: 3387-3396 - [c20]Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause:
Adaptive Sampling for Stochastic Risk-Averse Learning. NeurIPS 2020
2010 – 2019
- 2019
- [c19]Kfir Y. Levy, Andreas Krause:
Projection Free Online Learning over Smooth Sets. AISTATS 2019: 1458-1466 - [c18]Sebastian Curi, Kfir Y. Levy, Andreas Krause:
Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations. CDC 2019: 4115-4120 - [c17]Francis R. Bach, Kfir Y. Levy:
A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise. COLT 2019: 164-194 - [c16]Zalán Borsos, Sebastian Curi, Kfir Yehuda Levy, Andreas Krause:
Online Variance Reduction with Mixtures. ICML 2019: 705-714 - [c15]Ali Kavis, Kfir Y. Levy, Francis R. Bach, Volkan Cevher:
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization. NeurIPS 2019: 6257-6266 - [c14]Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Ian Goodfellow, Thomas Hofmann, Andreas Krause:
A Domain Agnostic Measure for Monitoring and Evaluating GANs. NeurIPS 2019: 12069-12079 - [i18]Francis R. Bach, Kfir Y. Levy:
A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise. CoRR abs/1902.01637 (2019) - [i17]Pragnya Alatur, Kfir Y. Levy, Andreas Krause:
Multi-Player Bandits: The Adversarial Case. CoRR abs/1902.08036 (2019) - [i16]Zalán Borsos, Sebastian Curi, Kfir Y. Levy, Andreas Krause:
Online Variance Reduction with Mixtures. CoRR abs/1903.12416 (2019) - [i15]Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause:
Adaptive Sampling for Stochastic Risk-Averse Learning. CoRR abs/1910.12511 (2019) - [i14]Ali Kavis, Kfir Y. Levy, Francis R. Bach, Volkan Cevher:
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization. CoRR abs/1910.13857 (2019) - 2018
- [c13]Zalan Borsos, Andreas Krause, Kfir Y. Levy:
Online Variance Reduction for Stochastic Optimization. COLT 2018: 324-357 - [c12]Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang:
Faster Rates for Convex-Concave Games. COLT 2018: 1595-1625 - [c11]Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause
:
An Online Learning Approach to Generative Adversarial Networks. ICLR (Poster) 2018 - [c10]Kfir Yehuda Levy, Alp Yurtsever, Volkan Cevher:
Online Adaptive Methods, Universality and Acceleration. NeurIPS 2018: 6501-6510 - [i13]Zalán Borsos, Andreas Krause, Kfir Y. Levy:
Online Variance Reduction for Stochastic Optimization. CoRR abs/1802.04715 (2018) - [i12]Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang:
Faster Rates for Convex-Concave Games. CoRR abs/1805.06792 (2018) - [i11]Sebastian Curi, Kfir Y. Levy, Andreas Krause:
Unsupervised Imitation Learning. CoRR abs/1806.07200 (2018) - [i10]Kfir Y. Levy, Alp Yurtsever, Volkan Cevher:
Online Adaptive Methods, Universality and Acceleration. CoRR abs/1809.02864 (2018) - [i9]Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Thomas Hofmann, Andreas Krause:
Evaluating GANs via Duality. CoRR abs/1811.05512 (2018) - 2017
- [c9]An Bian, Kfir Yehuda Levy, Andreas Krause, Joachim M. Buhmann:
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. NIPS 2017: 486-496 - [c8]Kfir Y. Levy:
Online to Offline Conversions, Universality and Adaptive Minibatch Sizes. NIPS 2017: 1613-1622 - [i8]Oren Anava, Kfir Y. Levy:
k*-Nearest Neighbors: From Global to Local. CoRR abs/1701.07266 (2017) - [i7]Kfir Y. Levy:
Online to Offline Conversions, Universality and Adaptive Minibatch Sizes. CoRR abs/1705.10499 (2017) - [i6]Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause:
An Online Learning Approach to Generative Adversarial Networks. CoRR abs/1706.03269 (2017) - [i5]An Bian, Kfir Y. Levy, Andreas Krause, Joachim M. Buhmann:
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. CoRR abs/1711.02515 (2017) - 2016
- [c7]Elad Hazan, Kfir Yehuda Levy, Shai Shalev-Shwartz:
On Graduated Optimization for Stochastic Non-Convex Problems. ICML 2016: 1833-1841 - [c6]Oren Anava, Kfir Y. Levy:
k*-Nearest Neighbors: From Global to Local. NIPS 2016: 4916-4924 - [i4]Kfir Y. Levy:
The Power of Normalization: Faster Evasion of Saddle Points. CoRR abs/1611.04831 (2016) - 2015
- [c5]Tomer Koren, Kfir Y. Levy:
Fast Rates for Exp-concave Empirical Risk Minimization. NIPS 2015: 1477-1485 - [c4]Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz:
Beyond Convexity: Stochastic Quasi-Convex Optimization. NIPS 2015: 1594-1602 - [i3]Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz:
On Graduated Optimization for Stochastic Non-Convex Problems. CoRR abs/1503.03712 (2015) - [i2]Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz:
Beyond Convexity: Stochastic Quasi-Convex Optimization. CoRR abs/1507.02030 (2015) - 2014
- [c3]Elad Hazan, Tomer Koren, Kfir Y. Levy:
Logistic Regression: Tight Bounds for Stochastic and Online Optimization. COLT 2014: 197-209 - [c2]Elad Hazan, Kfir Y. Levy:
Bandit Convex Optimization: Towards Tight Bounds. NIPS 2014: 784-792 - [i1]Elad Hazan, Tomer Koren, Kfir Y. Levy:
Logistic Regression: Tight Bounds for Stochastic and Online Optimization. CoRR abs/1405.3843 (2014) - 2011
- [c1]Kfir Y. Levy, Nahum Shimkin:
Unified Inter and Intra Options Learning Using Policy Gradient Methods. EWRL 2011: 153-164
Coauthor Index
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