| Beyond convexity: Stochastic quasi-convex optimization E Hazan, K Levy, S Shalev-Shwartz Advances in neural information processing systems 28, 2015 | 156 | 2015 |
| The power of normalization: Faster evasion of saddle points KY Levy arXiv preprint arXiv:1611.04831, 2016 | 110 | 2016 |
| Bandit convex optimization: Towards tight bounds E Hazan, K Levy Advances in Neural Information Processing Systems 27, 2014 | 97 | 2014 |
| On graduated optimization for stochastic non-convex problems E Hazan, KY Levy, S Shalev-Shwartz International conference on machine learning, 1833-1841, 2016 | 93 | 2016 |
| k*-nearest neighbors: From global to local O Anava, K Levy Advances in Neural Information Processing Systems, 2016 | 82 | 2016 |
| Online adaptive methods, universality and acceleration KY Levy, A Yurtsever, V Cevher Advances in neural information processing systems 31, 2018 | 80 | 2018 |
| An online learning approach to generative adversarial networks P Grnarova, KY Levy, A Lucchi, T Hofmann, A Krause arXiv preprint arXiv:1706.03269, 2017 | 73 | 2017 |
| Continuous dr-submodular maximization: Structure and algorithms A Bian, K Levy, A Krause, JM Buhmann Advances in Neural Information Processing Systems 30, 2017 | 71 | 2017 |
| A universal algorithm for variational inequalities adaptive to smoothness and noise F Bach, KY Levy Conference on learning theory, 164-194, 2019 | 65 | 2019 |
| Logistic regression: Tight bounds for stochastic and online optimization E Hazan, T Koren, KY Levy Conference on Learning Theory, 197-209, 2014 | 58 | 2014 |
| Fast rates for exp-concave empirical risk minimization T Koren, K Levy Advances in Neural Information Processing Systems 28, 2015 | 49 | 2015 |
| Online to offline conversions, universality and adaptive minibatch sizes K Levy Advances in Neural Information Processing Systems 30, 2017 | 48 | 2017 |
| Adaptive sampling for stochastic risk-averse learning S Curi, KY Levy, S Jegelka, A Krause Advances in Neural Information Processing Systems 33, 1036-1047, 2020 | 46 | 2020 |
| Unixgrad: A universal, adaptive algorithm with optimal guarantees for constrained optimization A Kavis, KY Levy, F Bach, V Cevher Advances in neural information processing systems 32, 2019 | 42 | 2019 |
| Faster rates for convex-concave games J Abernethy, KA Lai, KY Levy, JK Wang Conference On Learning Theory, 1595-1625, 2018 | 41 | 2018 |
| Unified inter and intra options learning using policy gradient methods KY Levy, N Shimkin Recent Advances in Reinforcement Learning: 9th European Workshop, EWRL 2011 …, 2012 | 37 | 2012 |
| A domain agnostic measure for monitoring and evaluating GANs P Grnarova, KY Levy, A Lucchi, N Perraudin, I Goodfellow, T Hofmann, ... Advances in Neural Information Processing Systems 32, 2019 | 36 | 2019 |
| Multi-player bandits: The adversarial case P Alatur, KY Levy, A Krause Journal of Machine Learning Research 21, 77, 2020 | 33 | 2020 |
| Explainable Artificial Intelligence (XAI) techniques for energy and power systems: Review, challenges and opportunities R Machlev, L Heistrene, M Perl, KY Levy, J Belikov, S Mannor, Y Levron Energy and AI, 100169, 2022 | 26 | 2022 |
| Online variance reduction for stochastic optimization Z Borsos, A Krause, KY Levy Conference On Learning Theory, 324-357, 2018 | 25 | 2018 |
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
