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Mingrui Liu
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Year
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
2372022
First-order convergence theory for weakly-convex-weakly-concave min-max problems
M Liu, H Rafique, Q Lin, T Yang
The Journal of Machine Learning Research 22 (1), 7651-7684, 2021
108*2021
Stochastic AUC Maximization with Deep Neural Networks
M Liu, Z Yuan, Y Ying, T Yang
International Conference on Learning Representations 2020, 2019
842019
Improved Schemes for Episodic Memory-based Lifelong Learning
Y Guo*, M Liu*, T Yang, T Rosing
Advances in Neural Information Processing Systems 33, 2020
742020
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
712019
Fast Stochastic AUC Maximization with -Convergence Rate
M Liu, X Zhang, Z Chen, X Wang, T Yang
International Conference on Machine Learning, 3189-3197, 2018
662018
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
622020
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
592017
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
402020
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
40*2018
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
272016
Adaptive accelerated gradient converging methods under holderian error bound condition
M Liu, T Yang
Advances in Neural Information Processing Systems 30, 2016
272016
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
262022
Understanding adamw through proximal methods and scale-freeness
Z Zhuang, M Liu, A Cutkosky, F Orabona
arXiv preprint arXiv:2202.00089, 2022
252022
Will bilevel optimizers benefit from loops
K Ji, M Liu, Y Liang, L Ying
Advances in Neural Information Processing Systems 35, 3011-3023, 2022
232022
Generalization guarantee of SGD for pairwise learning
Y Lei, M Liu, Y Ying
Advances in Neural Information Processing Systems 34, 21216-21228, 2021
192021
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
192018
Adam: A Stochastic Method with Adaptive Variance Reduction
M Liu, W Zhang, F Orabona, T Yang
arXiv preprint arXiv:2011.11985, 2020
182020
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
152020
Non-convex min–max optimization: provable algorithms and applications in machine learning (2018)
H Rafique, M Liu, Q Lin, T Yang
arXiv preprint arXiv:1810.02060, 1810
111810
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