| Why gradient clipping accelerates training: A theoretical justification for adaptivity AJ Jingzhao Zhang, Tianxing He, Suvrit Sra International Conference on Learning Representations 2020, 2020 | 226* | 2020 |
| Why are adaptive methods good for attention models? J Zhang, SP Karimireddy, A Veit, S Kim, S Reddi, S Kumar, S Sra Advances in Neural Information Processing Systems 33, 15383-15393, 2020 | 135* | 2020 |
| 3D computer-generated holography by non-convex optimization J Zhang, N Pégard, J Zhong, H Adesnik, L Waller Optica 4 (10), 1306-1313, 2017 | 119 | 2017 |
| Direct Runge-Kutta Discretization Achieves Acceleration J Zhang, A Mokhtari, S Sra, A Jadbabaie Advances in Neural Information Processing Systems 2018, 2018 | 90 | 2018 |
| Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? T He, J Zhang, Z Zhou, J Glass arXiv preprint arXiv:1905.10617, 2019 | 39* | 2019 |
| Complexity of finding stationary points of nonconvex nonsmooth functions J Zhang, H Lin, S Jegelka, S Sra, A Jadbabaie International Conference on Machine Learning, 11173-11182, 2020 | 34 | 2020 |
| R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate J Zhang, H Zhang, S Sra arXiv preprint arXiv:1811.04194, 2018 | 32 | 2018 |
| Coping with label shift via distributionally robust optimisation J Zhang, A Menon, A Veit, S Bhojanapalli, S Kumar, S Sra arXiv preprint arXiv:2010.12230, 2020 | 27 | 2020 |
| Fast federated learning in the presence of arbitrary device unavailability X Gu, K Huang, J Zhang, L Huang Advances in Neural Information Processing Systems 34, 12052-12064, 2021 | 20 | 2021 |
| Complexity lower bounds for nonconvex-strongly-concave min-max optimization H Li, Y Tian, J Zhang, A Jadbabaie Advances in Neural Information Processing Systems 34, 1792-1804, 2021 | 19 | 2021 |
| Understanding the unstable convergence of gradient descent K Ahn, J Zhang, S Sra International Conference on Machine Learning, 247-257, 2022 | 17 | 2022 |
| A probe towards understanding gan and vae models L Mi, M Shen, J Zhang arXiv preprint arXiv:1812.05676, 2018 | 17 | 2018 |
| Provably efficient algorithms for multi-objective competitive rl T Yu, Y Tian, J Zhang, S Sra International Conference on Machine Learning, 12167-12176, 2021 | 14 | 2021 |
| Achieving Acceleration in Distributed Optimization via Direct Discretization of the Heavy-Ball ODE J Zhang, CA Uribe, A Mokhtari, A Jadbabaie 2019 American Control Conference, 2018 | 12 | 2018 |
| Minimax in Geodesic Metric Spaces: Sion's Theorem and Algorithms P Zhang, J Zhang, S Sra arXiv preprint arXiv:2202.06950, 2022 | 6 | 2022 |
| Acceleration in First Order Quasi-strongly Convex Optimization by ODE Discretization J Zhang, S Sra, A Jadbabaie 2019 Conference on Decision and Control, 2019 | 6 | 2019 |
| Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity J Zhang, H Lin, S Das, S Sra, A Jadbabaie ICML 2022, 2020 | 5* | 2020 |
| Holographic temporal focusing for 3D photo-activation with single neuron resolution N Pégard, A Mardinly, J Zhang, S Sridharan, L Waller, H Adesnik Optics and the Brain, BrM3B. 2, 2017 | 2 | 2017 |
| On Bilevel Optimization without Lower-level Strong Convexity L Chen, J Xu, J Zhang arXiv preprint arXiv:2301.00712, 2023 | 1 | 2023 |
| Theory and Algorithms for Diffusion Processes on Riemannian Manifolds X Cheng, J Zhang, S Sra arXiv preprint arXiv:2204.13665, 2022 | 1 | 2022 |
Suvrit SraMITVerified email at mit.edu
