Mingrui Liu

According to our database, Mingrui Liu authored at least 55 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Beyond Single-Model Views for Deep Learning: Optimization versus Generalizability of Stochastic Optimization Algorithms.

Toki Tahmid Inan, Mingrui Liu, Amarda Shehu

CoRR, 2024

Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis.

Jie Hao, Xiaochuan Gong, Mingrui Liu

CoRR, 2024

Optimizing File Systems on Heterogeneous Memory by Integrating DRAM Cache with Virtual Memory Management.

Yubo Liu, Yuxin Ren, Mingrui Liu, Hongbo Li, Hanjun Guo, Xie Miao, Xinwei Hu, Haibo Chen

Proceedings of the 22nd USENIX Conference on File and Storage Technologies, 2024

Algorithmic Foundation of Federated Learning with Sequential Data.

Mingrui Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Heterogeneous Graph Transformer for Meta-structure Learning with Application in Text Classification.

Shuhai Wang, Xin Liu, Xiao Pan, Hanjie Xu, Mingrui Liu

ACM Trans. Web, August, 2023

LESS-Map: Lightweight and Evolving Semantic Map in Parking Lots for Long-term Self-Localization.

Mingrui Liu, Xinyang Tang, Yeqiang Qian, Jiming Chen, Liang Li

CoRR, 2023

Stability and Generalization for Minibatch SGD and Local SGD.

Yunwen Lei, Tao Sun, Mingrui Liu

CoRR, 2023

AUC Maximization in Imbalanced Lifelong Learning.

Xiangyu Zhu, Jie Hao, Yunhui Guo, Mingrui Liu

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm.

Jie Hao, Kaiyi Ji, Mingrui Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds.

Michael Crawshaw, Yajie Bao, Mingrui Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization.

Yajie Bao, Amarda Shehu, Mingrui Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Age Feature Enhanced Neural Network for RUL Estimation of Power Electronic Devices.

Zhonghai Lu, Rui Shi, Chao Guo, Mingrui Liu

Proceedings of the IEEE International Conference on Prognostics and Health Management, 2023

EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data.

Michael Crawshaw, Yajie Bao, Mingrui Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Cache or Direct Access? Revitalizing Cache in Heterogeneous Memory File System.

Yubo Liu, Yuxin Ren, Mingrui Liu, Hanjun Guo, Xie Miao, Xinwei Hu

Proceedings of the 1st Workshop on Disruptive Memory Systems, 2023

A Generalized Propensity Learning Framework for Unbiased Post-Click Conversion Rate Estimation.

Yuqing Zhou, Tianshu Feng, Mingrui Liu, Ziwei Zhu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Infrared video behavior recognition algorithm based on AGX Xavier environment.

Mingrui Liu, Xiaogang Wang, Yang Wei, Jiayi Zhou, Rui Song, Zewei Lian

Proceedings of the CAA Symposium on Fault Detection, 2023

2022

Quantum Dots-Functionalized Encryption Camera for Text Image Security Protection.

Xue Li, Jia Peng, Tao Zhang, Mingrui Liu, Ying Fu, Haizheng Zhong, Jun Zhang

Adv. Intell. Syst., December, 2022

Understanding AdamW through Proximal Methods and Scale-Freeness.

Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona

Trans. Mach. Learn. Res., 2022

Weakly-convex-concave min-max optimization: provable algorithms and applications in machine learning.

Hassan Rafique, Mingrui Liu, Qihang Lin, Tianbao Yang

Optim. Methods Softw., 2022

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks.

Mingrui Liu, Zhenxun Zhuang, Yunwei Lei, Chunyang Liao

CoRR, 2022

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks.

Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Will Bilevel Optimizers Benefit from Loops.

Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robustness to Unbounded Smoothness of Generalized SignSGD.

Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fast Composite Optimization and Statistical Recovery in Federated Learning.

Yajie Bao, Michael Crawshaw, Shan Luo, Mingrui Liu

Proceedings of the International Conference on Machine Learning, 2022

DSFL: Dynamic Sparsification for Federated Learning.

Mahdi Beitollahi, Mingrui Liu, Ning Lu

Proceedings of the 5th International Conference on Communications, 2022

F-Measure Optimization for Multi-class, Imbalanced Emotion Classification Tasks.

Toki Tahmid Inan, Mingrui Liu, Amarda Shehu

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

On Inferring User Socioeconomic Status with Mobility Records.

Zheng Wang, Mingrui Liu, Cheng Long, Qianru Zhang, Jiangneng Li, Chunyan Miao

Proceedings of the IEEE International Conference on Big Data, 2022

On the Initialization for Convex-Concave Min-max Problems.

Mingrui Liu, Francesco Orabona

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

On the Last Iterate Convergence of Momentum Methods.

Xiaoyu Li, Mingrui Liu, Francesco Orabona

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021

Asynchronous Decentralized Distributed Training of Acoustic Models.

Xiaodong Cui, Wei Zhang, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, David S. Kung

IEEE ACM Trans. Audio Speech Lang. Process., 2021

First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems.

Mingrui Liu, Hassan Rafique, Qihang Lin, Tianbao Yang

J. Mach. Learn. Res., 2021

Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent.

Wei Zhang, Mingrui Liu, Yu Feng, Xiaodong Cui, Brian Kingsbury, Yuhai Tu

CoRR, 2021

A Parameter-free Algorithm for Convex-concave Min-max Problems.

Mingrui Liu, Francesco Orabona

CoRR, 2021

Generalization Guarantee of SGD for Pairwise Learning.

Yunwen Lei, Mingrui Liu, Yiming Ying

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Adam⁺: A Stochastic Method with Adaptive Variance Reduction.

Mingrui Liu, Wei Zhang, Francesco Orabona, Tianbao Yang

CoRR, 2020

The game of Cops and Robbers on directed graphs with forbidden subgraphs.

Mingrui Liu

CoRR, 2020

A Decentralized Parallel Algorithm for Training Generative Adversarial Nets.

Mingrui Liu, Wei Zhang, Youssef Mroueh, Xiaodong Cui, Jarret Ross, Tianbao Yang, Payel Das

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improved Schemes for Episodic Memory-based Lifelong Learning.

Yunhui Guo, Mingrui Liu, Tianbao Yang, Tajana Rosing

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks.

Zhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang

Proceedings of the 37th International Conference on Machine Learning, 2020

Stochastic AUC Maximization with Deep Neural Networks.

Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang

Proceedings of the 8th International Conference on Learning Representations, 2020

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

Proceedings of the 8th International Conference on Learning Representations, 2020

Improving Efficiency in Large-Scale Decentralized Distributed Training.

Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David S. Kung, Michael Picheny

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Decentralized Parallel Algorithm for Training Generative Adversarial Nets.

Mingrui Liu, Youssef Mroueh, Wei Zhang, Xiaodong Cui, Jerret Ross, Tianbao Yang, Payel Das

CoRR, 2019

Learning with Long-term Remembering: Following the Lead of Mixed Stochastic Gradient.

Yunhui Guo, Mingrui Liu, Tianbao Yang, Tajana Rosing

CoRR, 2019

The Cop Number of Graphs with Forbidden Induced Subgraphs.

Mingrui Liu

CoRR, 2019

A Blackboard Sharing Mechanism for Community Cyber Threat Intelligence Based on Multi-Agent System.

Yue Lin, He Wang, Bowen Yang, Mingrui Liu, Yin Li, Yuqing Zhang

Proceedings of the Machine Learning for Cyber Security - Second International Conference, 2019

2018

Non-Convex Min-Max Optimization: Provable Algorithms and Applications in Machine Learning.

Hassan Rafique, Mingrui Liu, Qihang Lin, Tianbao Yang

CoRR, 2018

IntLIM: integration using linear models of metabolomics and gene expression data.

Jalal K. Siddiqui, Elizabeth Baskin, Mingrui Liu, Carmen Z. Cantemir-Stone, Bofei Zhang, Russell Bonneville, Joseph P. McElroy, Kevin R. Coombes, Ewy A Mathé

BMC Bioinform., 2018

Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization.

Xiaoxuan Zhang, Mingrui Liu, Xun Zhou, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions.

Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adaptive Negative Curvature Descent with Applications in Non-convex Optimization.

Mingrui Liu, Zhe Li, Xiaoyu Wang, Jinfeng Yi, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

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, 2018

2017

Stochastic Non-convex Optimization with Strong High Probability Second-order Convergence.

Mingrui Liu, Tianbao Yang

CoRR, 2017

ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization.

Yi Xu, Mingrui Liu, Qihang Lin, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition.

Mingrui Liu, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017