Weakly-convex–concave min–max optimization: provable algorithms and applications in machine learning H Rafique, M Liu, Q Lin, T Yang
Optimization Methods and Software 37 (3), 1087-1121, 2022
278 2022 First-order convergence theory for weakly-convex-weakly-concave min-max problems M Liu, H Rafique, Q Lin, T Yang
Journal of Machine Learning Research 22 (169), 1-34, 2021
119 * 2021 Stochastic AUC Maximization with Deep Neural Networks M Liu, Z Yuan, Y Ying, T Yang
International Conference on Learning Representations 2020, 2019
104 2019 Improved Schemes for Episodic Memory-based Lifelong Learning Y Guo*, M Liu*, T Yang, T Rosing
Advances in Neural Information Processing Systems 33, 2020
99 * 2020 A decentralized parallel algorithm for training generative adversarial nets M Liu, W Zhang, Y Mroueh, X Cui, J Ross, T Yang, P Das
Advances in Neural Information Processing Systems 33, 11056-11070, 2020
82 2020 Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets M Liu, Y Mroueh, J Ross, W Zhang, X Cui, P Das, T Yang
International Conference on Learning Representations 2020, 2019
78 2019 Fast Stochastic AUC Maximization with M Liu, X Zhang, Z Chen, X Wang, T Yang
International Conference on Machine Learning, 3189-3197, 2018
71 2018 Understanding adamw through proximal methods and scale-freeness Z Zhuang, M Liu, A Cutkosky, F Orabona
Transactions on machine learning research, 2022
68 2022 ADMM without a fixed penalty parameter: Faster convergence with new adaptive penalization Y Xu, M Liu, Q Lin, T Yang
Advances in neural information processing systems 30, 2017
63 2017 Robustness to unbounded smoothness of generalized signsgd M Crawshaw, M Liu, F Orabona, W Zhang, Z Zhuang
Advances in neural information processing systems 35, 9955-9968, 2022
58 2022 Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks Z Guo, M Liu, Z Yuan, L Shen, W Liu, T Yang
International Conference on Machine Learning 2020, 2020
46 2020 Adaptive negative curvature descent with applications in non-convex optimization M Liu, Z Li, X Wang, J Yi, T Yang
Advances in Neural Information Processing Systems, 4853-4862, 2018
43 * 2018 Will bilevel optimizers benefit from loops K Ji, M Liu, Y Liang, L Ying
Advances in Neural Information Processing Systems 35, 3011-3023, 2022
37 2022 Generalization guarantee of SGD for pairwise learning Y Lei, M Liu, Y Ying
Advances in neural information processing systems 34, 21216-21228, 2021
31 2021 Adam M Liu, W Zhang, F Orabona, T Yang
arXiv preprint arXiv:2011.11985, 2020
31 2020 Adaptive accelerated gradient converging methods under holderian error bound condition M Liu, T Yang
Advances in Neural Information Processing Systems 30, 2016
28 2016 Spatiotemporal dynamics in a network composed of neurons with different excitabilities and excitatory coupling WW Xiao, HG Gu, MR Liu
Science China Technological Sciences 59, 1943-1952, 2016
27 2016 Fast rates of erm and stochastic approximation: Adaptive to error bound conditions M Liu, X Zhang, L Zhang, R Jin, T Yang
Advances in Neural Information Processing Systems 30, 2018
22 2018 A communication-efficient distributed gradient clipping algorithm for training deep neural networks M Liu, Z Zhuang, Y Lei, C Liao
Advances in Neural Information Processing Systems 35, 26204-26217, 2022
20 2022 Improving efficiency in large-scale decentralized distributed training W Zhang, X Cui, A Kayi, M Liu, U Finkler, B Kingsbury, G Saon, Y Mroueh, ...
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
17 2020 
Tianbao YangTexas A&M UniversityAdresse e-mail validée de tamu.edu
