Variance reduction for matrix games Y Carmon, Y Jin, A Sidford, K Tian
Advances in Neural Information Processing Systems 32, 2019
85 2019 Efficiently solving MDPs with stochastic mirror descent Y Jin, A Sidford
International Conference on Machine Learning, 4890-4900, 2020
84 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
50 2020 VO A Agarwal, Y Jin, T Zhang
The Thirty Sixth Annual Conference on Learning Theory, 987-1063, 2023
47 2023 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
39 2022 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
39 2020 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
37 2022 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
36 2022 Stochastic Bias-Reduced Gradient Methods H Asi, Y Carmon, J Arun, Y Jin, A Sidford
arXiv preprint arXiv:2106.09481, 2021
36 2021 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
29 2021 Towards tight bounds on the sample complexity of average-reward MDPs Y Jin, A Sidford
International Conference on Machine Learning, 5055-5064, 2021
29 2021 The complexity of infinite-horizon general-sum stochastic games Y Jin, V Muthukumar, A Sidford
arXiv preprint arXiv:2204.04186, 2022
23 2022 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
18 2023 Regularized box-simplex games and dynamic decremental bipartite matching A Jambulapati, Y Jin, A Sidford, K Tian
arXiv preprint arXiv:2204.12721, 2022
17 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
17 2017 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
15 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
13 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
13 2019 A unified framework for multi-distribution density ratio estimation L Yu, Y Jin, S Ermon
arXiv preprint arXiv:2112.03440, 2021
7 2021 A whole new ball game: A primal accelerated method for matrix games and minimizing the maximum of smooth functions Y Carmon, A Jambulapati, Y Jin, A Sidford
Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2024
3 2024 
Aaron SidfordStanford UniversityEmail yang diverifikasi di stanford.edu