About Me

Bio:

Yawei Zhao is now working at Medical Big Data Research Center of Chinese PLA General Hospital & National Engineering Research Center for the Application Technology of Medical Big Data, Beijing, 100853, China.

He received the Ph.D degree in Computer Science from the National University of Defense Technology, China in 2020. He received his B.E. degree and M.S. degree in Computer Science from the National University of Defense Technology, China, in 2013 and 2015, respectively. His research interests include time-series analysis, medical data analysis, and federated learning.

Contact me:

E-mail: csyawei.zhao@gmail.com; zhaoyawei09@163.com.

Phone: +86 13691485488.

Other links: Yawei's Google Scholar; Yawei's Research Gate.

News

11/28/2022

I begin postdoc at National Engineering Research Center for the Application Technology of Medical Big Data.

01/01/2020

It is my honor to get the Kwang-Hua Scholarship. Thanks to Kwang-Hua Education Foundation.

11/27/2019

I finish the visiting in Ji Liu's team at University of Rochester. Thanks to Ji and all friends. I have learned a lot at UR. This is one of my best memories.

11/27/2017

I am going to visit Ji Liu's team at University of Rochester, and will continue my Ph.D project under his guidance for the next two years. Thanks to CSC Scholarship.

07/01/2016

I am going to visit Jun Zhu's team at Tsinghus University, and will continue my Ph.D project under his guidance for the next three months.

01/01/2016

We get some awards now, thanks for the great team.

[数模竞赛获奖证书] [物联网竞赛获奖证书]

Publications

Yemao Xu, Dezun Dong, Yawei Zhao, et al.,OD-SGD: One-step Delay Stochastic Gradient Descent for Distributed Training. ACM Transactions on Architecture and Code Optimization (TACO), 2020.
Wendi Wu, Yawei Zhao, En Zhu, et al.,A Theoretical Revisit to Linear Convergence for Saddle Point Problems. ACM Transactions on Intelligent Systems and Technology (TIST), 2020.
Shangsen Li, Lailong Luo, Deke Guo, and Yawei Zhao,Multiset Synchronization with Counting Cuckoo Filters. International Conference on Wireless Algorithms, Systems and Applications (WASA), 2020.
Yawei Zhao, Shuang Qiu, Kuan Li, Lailong Luo, Jianping Yin, Ji Liu,Proximal Online Gradient is Optimum for Dynamic Regret: A General Lower Bound. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020. [paper] [comments]
Yawei Zhao, En Zhu, Xinwang Liu, et al.,Simultaneous clustering and optimization for evolving datasets. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. [paper] [comments]
Yawei Zhao, Qian Zhao, Xingxing Zhang, et al.,Understand Dynamic Regret with Switching Cost for Online Decision Making. ACM Transactions on Intelligent Systems and Technology (TIST), 2020. [paper] [comments]
Yawei Zhao, Kai Xu, Xinwang Liu, et al.,Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019. [paper] [comments]
Yawei Zhao, Yuewei Ming, Xinwang Liu, et al.,Variance Reduced K-means Clustering. Thirty-Second AAAI Conference on Artificial Intelligence, 2018. [paper] [code] [comments]
Yawei Zhao, Yuewei Ming, Xinwang Liu, et al.,Large-scale k-means clustering via variance reduction. Neurocomputing, 2018. [paper] [code] [comments]
Yawei Zhao, Deke Guo, Jia Xu, et al.,Cooperative allocation of tasks and scheduling of sampling intervals for maximizing data sharing in WSNs. ACM Transactions on Sensor Networks (TOSN), 2016. [paper] [comments]
Yawei Zhao, Fei Cai, Junjie Xie, et al.,A New DHT Supporting Multi-Attribute Queries for Grid Information Services. IEEE International Conference on High Performance Computing and Communications (HPCC), 2013. [paper] [comments]
Sihang Zhou, Xinwang Liu, Jiyuan Liu, Xifeng Guo, Yawei Zhao, et al.,Multi-View Spectral Clustering with Optimal Neighborhood Laplacian Matrix. AAAI Conference on Artificial Intelligence, 2020.
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao, Yawei Zhao,ProLFA: Representative Prototype Selection for Local Feature Aggregation. Neurocomputing, 2020.
Yuewei Ming, Yawei Zhao, Chengkun Wu, et al.,Distributed and asynchronous Stochastic Gradient Descent with variance reduction. Neurocomputing, 2019. [paper] [comments]
Erxue Min, Yawei Zhao, Jun Long, et al.,SVRG with adaptive epoch size. International Joint Conference on Neural Networks (IJCNN), 2016. [paper] [comments]

Softwares

Variance Reduced K-means Clustering Methods. [Source code]
The acceleration is significant. For example, we conduct the variance reduced k-means clustering methods on the dataset: Pittsbour. Then we obtain more than 5x speedup.