| The adaptive complexity of maximizing a submodular function E Balkanski, Y Singer Proceedings of the 50th annual ACM SIGACT symposium on theory of computing …, 2018 | 126 | 2018 |
| An exponential speedup in parallel running time for submodular maximization without loss in approximation E Balkanski, A Rubinstein, Y Singer Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 104 | 2019 |
| The limitations of optimization from samples E Balkanski, A Rubinstein, Y Singer Proceedings of the 49th annual acm sigact symposium on theory of computing …, 2017 | 66 | 2017 |
| Non-monotone submodular maximization in exponentially fewer iterations E Balkanski, A Breuer, Y Singer Advances in Neural Information Processing Systems 31, 2018 | 59 | 2018 |
| The power of optimization from samples E Balkanski, A Rubinstein, Y Singer Advances in Neural Information Processing Systems 29, 2016 | 52 | 2016 |
| Learning-augmented mechanism design: Leveraging predictions for facility location P Agrawal, E Balkanski, V Gkatzelis, T Ou, X Tan Proceedings of the 23rd ACM Conference on Economics and Computation, 497-528, 2022 | 44 | 2022 |
| The FAST algorithm for submodular maximization A Breuer, E Balkanski, Y Singer International Conference on Machine Learning, 1134-1143, 2020 | 44 | 2020 |
| An optimal approximation for submodular maximization under a matroid constraint in the adaptive complexity model E Balkanski, A Rubinstein, Y Singer Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 43 | 2019 |
| Parallelization does not accelerate convex optimization: Adaptivity lower bounds for non-smooth convex minimization E Balkanski, Y Singer arXiv preprint arXiv:1808.03880, 2018 | 42 | 2018 |
| Approximation guarantees for adaptive sampling E Balkanski, Y Singer International Conference on Machine Learning, 384-393, 2018 | 37 | 2018 |
| Learning sparse combinatorial representations via two-stage submodular maximization E Balkanski, B Mirzasoleiman, A Krause, Y Singer International Conference on Machine Learning, 2207-2216, 2016 | 37 | 2016 |
| Bayesian budget feasibility with posted pricing E Balkanski, JD Hartline Proceedings of the 25th International Conference on World Wide Web, 189-203, 2016 | 35 | 2016 |
| Statistical cost sharing E Balkanski, U Syed, S Vassilvitskii Advances in Neural Information Processing Systems 30, 2017 | 31 | 2017 |
| Simultaneous cake cutting E Balkanski, S Brânzei, D Kurokawa, A Procaccia Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 28 | 2014 |
| Strategyproof scheduling with predictions E Balkanski, V Gkatzelis, X Tan arXiv preprint arXiv:2209.04058, 2022 | 27 | 2022 |
| The importance of communities for learning to influence E Balkanski, N Immorlica, Y Singer Advances in Neural Information Processing Systems 30, 2017 | 24 | 2017 |
| Deterministic Budget-Feasible Clock Auctions∗ E Balkanski, P Garimidi, V Gkatzelis, D Schoepflin, X Tan Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 19 | 2022 |
| The sample complexity of optimizing a convex function E Balkanski, Y Singer Conference on Learning Theory, 275-301, 2017 | 17 | 2017 |
| A lower bound for parallel submodular minimization E Balkanski, Y Singer Proceedings of the 52nd annual ACM SIGACT symposium on theory of computing …, 2020 | 16 | 2020 |
| Learning to optimize combinatorial functions N Rosenfeld, E Balkanski, A Globerson, Y Singer International Conference on Machine Learning, 4374-4383, 2018 | 16 | 2018 |
Yaron SingerHarvard UniversityE-mailová adresa ověřena na: seas.harvard.edu