Stebėti
Haochuan Li
Haochuan Li
MIT EECS
Patvirtintas el. paštas mit.edu
Pavadinimas
Cituota
Cituota
Metai
Gradient descent finds global minima of deep neural networks
S Du, J Lee, H Li, L Wang, X Zhai
International conference on machine learning, 1675-1685, 2019
12782019
Convergence of adversarial training in overparametrized neural networks
R Gao, T Cai, H Li, CJ Hsieh, L Wang, JD Lee
Advances in Neural Information Processing Systems 32, 2019
1412019
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
332021
Convergence of Adam under Relaxed Assumptions
H Li, A Jadbabaie, A Rakhlin
arXiv preprint arXiv:2304.13972, 2023
202023
Byzantine-robust federated linear bandits
A Jadbabaie, H Li, J Qian, Y Tian
2022 IEEE 61st Conference on Decision and Control (CDC), 5206-5213, 2022
132022
Convex and non-convex optimization under generalized smoothness
H Li, J Qian, Y Tian, A Rakhlin, A Jadbabaie
Advances in Neural Information Processing Systems 36, 2024
102024
Variance-reduced clipping for non-convex optimization
A Reisizadeh, H Li, S Das, A Jadbabaie
arXiv preprint arXiv:2303.00883, 2023
92023
Tight analysis of extra-gradient and optimistic gradient methods for nonconvex minimax problems
P Mahdavinia, Y Deng, H Li, M Mahdavi
Advances in Neural Information Processing Systems 35, 31213-31225, 2022
92022
Neural network weights do not converge to stationary points: An invariant measure perspective
J Zhang, H Li, S Sra, A Jadbabaie
International Conference on Machine Learning, 26330-26346, 2022
72022
On convergence of gradient descent ascent: A tight local analysis
H Li, F Farnia, S Das, A Jadbabaie
International Conference on Machine Learning, 12717-12740, 2022
52022
On the Complexity of Nonconvex-Strongly-Concave Smooth Minimax Optimization Using First-Order Methods
H Li
Massachusetts Institute of Technology, 2021
2021
Randomness in Deconvolutional Networks for Visual Representation
K He, J Wang, H Li, Y Shu, M Zhang, M Zhu, L Wang, JE Hopcroft
arXiv preprint arXiv:1704.00330, 2017
2017
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