About Me
I am a fourth year PhD student at Department of Computer Science, The University of Iowa. My advisor is Prof. Tianbao Yang.
Research
My research interests are machine learning, optimization and learning theory.
News
- (Dec 2019) Two papers were accepted by ICLR 2020.
- (Sep 2018) Three papers were accepted by NeurIPS 2018.
- (May 2018) One paper was accepted by ICML 2018.
Preprints
- (New! )
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets
Mingrui Liu, Youssef Mroueh, Wei Zhang, Xiaodong Cui, Jerret Ross, Tianbao Yang, Payel Das.
arXiv Preprint:1910.12999
- (New! )
Solving Weakly-Convex-Weakly-Concave Saddle Point Problems as Weakly-Monotone Variational Inequality
with Qihang Lin, Hassan Rafique, Tianbao Yang.
arXiv Preprint:1810.10207
- (New! )
Non-Convex Min-Max Optimization: Provable Algorithms and Applications in Machine Learning
Hassan Rafique, Mingrui Liu, Qihang Lin, Tianbao Yang.
arXiv Preprint:1810.02060
-
On Noisy Negative Curvature Descent: Competing with Gradient Descent for Faster Non-convex Optimization
Mingrui Liu, Tianbao Yang.
arXiv Preprint:1709.08571 [a short version has been accepted by NeurIPS 2018]
Publications
- (New! )
Stochastic AUC Maximization with Deep Neural Networks
Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang.
To Appear at 8th International Conference on Learning Representations, 2020. (ICLR 2020)
-
(New! ) Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets
Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang.
To Appear at 8th International Conference on Learning Representations, 2020. (ICLR 2020)
-
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization
Mingrui Liu, Zhe Li, Xiaoyu Wang, Jinfeng Yi, Tianbao Yang.
Advances in Neural Information Processing Systems 31, 2018. (NeurIPS 2018)
[arXiv Version] [Supplement] [Bibtex] [Poster]
-
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions
Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang.
Advances in Neural Information Processing Systems 31, 2018. (NeurIPS 2018)
[arXiv Version] [Supplement] [Bibtex] [Poster]
-
Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization
Mingrui Liu*, Xiaoxuan Zhang*, Xun Zhou, Tianbao Yang. (*: equal contribution)
Advances in Neural Information Processing Systems 31, 2018. (NeurIPS 2018)
[Supplement]
-
Fast Stochastic AUC Maximization with O(1/n) Convergence Rate
Mingrui Liu, Xiaoxuan Zhang, Zaiyi Chen, Xiaoyu Wang, Tianbao Yang.
Proceedings of the 35th International Conference on Machine Learning 35, 2018. (ICML 2018)
[Supplement] [Bibtex] [Poster] [Code]
-
Stochastic Non-convex Optimization with Strong
High Probability Second-order Convergence
Mingrui Liu, Tianbao Yang.
NIPS workshop on Optimization for Machine Learning, 2017.
[arXiv Version]
-
Adaptive Accelerated Gradient Converging Methods under Holderian Error Bound Condition
Mingrui Liu, Tianbao Yang.
Advances In Neural Information Processing Systems 30, 2017. (NIPS 2017)
[Supplement] [Bibtex] [Poster] [arXiv Version]
-
ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization
Yi Xu, Mingrui Liu, Qihang Lin, Tianbao Yang.
Advances In Neural Information Processing Systems 30, 2017. (NIPS 2017)
[Supplement] [Bibtex] [Poster]
Working Experience
Miscellaneous
Last update: 12-09-2019