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Mingrui Liu
Mingrui Liu
在 gmu.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
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, 1-35, 2021
156*2021
First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems.
M Liu, H Rafique, Q Lin, T Yang
J. Mach. Learn. Res. 22, 169:1-169:34, 2021
80*2021
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
452018
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
432019
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
392017
Stochastic AUC Maximization with Deep Neural Networks
M Liu, Z Yuan, Y Ying, T Yang
International Conference on Learning Representations 2020, 2019
332019
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
322020
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
31*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 (12), 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
242016
Improved Schemes for Episodic Memory-based Lifelong Learning
Y Guo*, M Liu*, T Yang, T Rosing
Advances in Neural Information Processing Systems 33, 2020
23*2020
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
162020
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
162018
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
142020
Adam: A Stochastic Method with Adaptive Variance Reduction
M Liu, W Zhang, F Orabona, T Yang
arXiv preprint arXiv:2011.11985, 2020
72020
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
71810
Faster online learning of optimal threshold for consistent F-measure optimization
X Zhang*, M Liu*, X Zhou, T Yang
Advances in Neural Information Processing Systems, 3889-3899, 2018
62018
Generalization guarantee of SGD for pairwise learning
Y Lei, M Liu, Y Ying
Advances in Neural Information Processing Systems 34, 21216-21228, 2021
42021
Stochastic non-convex optimization with strong high probability second-order convergence
M Liu, T Yang
arXiv preprint arXiv:1710.09447, 2017
22017
Will Bilevel Optimizers Benefit from Loops
K Ji, M Liu, Y Liang, L Ying
arXiv preprint arXiv:2205.14224, 2022
12022
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