| Variance reduction for matrix games Y Carmon, Y Jin, A Sidford, K Tian Advances in Neural Information Processing Systems 32, 2019 | 75 | 2019 |
| Efficiently solving MDPs with stochastic mirror descent Y Jin, A Sidford International Conference on Machine Learning, 4890-4900, 2020 | 72 | 2020 |
| Acceleration with a ball optimization oracle Y Carmon, A Jambulapati, Q Jiang, Y Jin, YT Lee, A Sidford, K Tian Advances in Neural Information Processing Systems 33, 19052-19063, 2020 | 45 | 2020 |
| VOL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation A Agarwal, Y Jin, T Zhang The Thirty Sixth Annual Conference on Learning Theory, 987-1063, 2023 | 40 | 2023 |
| Coordinate methods for matrix games Y Carmon, Y Jin, A Sidford, K Tian 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 36 | 2020 |
| Sharper rates for separable minimax and finite sum optimization via primal-dual extragradient methods Y Jin, A Sidford, K Tian Conference on Learning Theory, 4362-4415, 2022 | 34 | 2022 |
| Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space∗ S Assadi, A Jambulapati, Y Jin, A Sidford, K Tian Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 34 | 2022 |
| Stochastic Bias-Reduced Gradient Methods H Asi, Y Carmon, J Arun, Y Jin, A Sidford arXiv preprint arXiv:2106.09481, 2021 | 33 | 2021 |
| Optimal and adaptive monteiro-svaiter acceleration Y Carmon, D Hausler, A Jambulapati, Y Jin, A Sidford Advances in Neural Information Processing Systems 35, 20338-20350, 2022 | 26 | 2022 |
| Thinking inside the ball: Near-optimal minimization of the maximal loss Y Carmon, A Jambulapati, Y Jin, A Sidford Conference on Learning Theory, 866-882, 2021 | 23 | 2021 |
| Towards tight bounds on the sample complexity of average-reward MDPs Y Jin, A Sidford International Conference on Machine Learning, 5055-5064, 2021 | 23 | 2021 |
| The complexity of infinite-horizon general-sum stochastic games Y Jin, V Muthukumar, A Sidford arXiv preprint arXiv:2204.04186, 2022 | 19 | 2022 |
| Regularized box-simplex games and dynamic decremental bipartite matching A Jambulapati, Y Jin, A Sidford, K Tian arXiv preprint arXiv:2204.12721, 2022 | 16 | 2022 |
| Maximum matchings and minimum dominating sets in Apollonian networks and extended Tower of Hanoi graphs Y Jin, H Li, Z Zhang Theoretical Computer Science 703, 37-54, 2017 | 16 | 2017 |
| Quantum speedups for zero-sum games via improved dynamic Gibbs sampling A Bouland, YM Getachew, Y Jin, A Sidford, K Tian International Conference on Machine Learning, 2932-2952, 2023 | 14 | 2023 |
| Recapp: Crafting a more efficient catalyst for convex optimization Y Carmon, A Jambulapati, Y Jin, A Sidford International Conference on Machine Learning, 2658-2685, 2022 | 12 | 2022 |
| Principal component projection and regression in nearly linear time through asymmetric svrg Y Jin, A Sidford Advances in neural information processing systems 32, 2019 | 10 | 2019 |
| Resqueing parallel and private stochastic convex optimization Y Carmon, A Jambulapati, Y Jin, YT Lee, D Liu, A Sidford, K Tian 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS …, 2023 | 9 | 2023 |
| A unified framework for multi-distribution density ratio estimation L Yu, Y Jin, S Ermon arXiv preprint arXiv:2112.03440, 2021 | 5 | 2021 |
| Moments, Random Walks, and Limits for Spectrum Approximation Y Jin, C Musco, A Sidford, AV Singh The Thirty Sixth Annual Conference on Learning Theory, 5373-5394, 2023 | 2 | 2023 |
Aaron SidfordStanford UniversityVerified email at stanford.edu
