Jiazhou Wang

According to our database, Jiazhou Wang authored at least 11 papers between 2017 and 2024.

Collaborative distances:

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

2024

A Dynamic and Static Combined State Recovery Method Against FDI Attacks in Power Grids.

Jiazhou Wang, Jue Tian, Nanpeng Yu, Yang Liu, Haichuan Zhang, Yadong Zhou, Ting Liu

IEEE Trans. Smart Grid, November, 2024

HELLINGER-UCB: A novel algorithm for stochastic multi-armed bandit problem and cold start problem in recommender system.

Ruibo Yang, Jiazhou Wang, Andrew Mullhaupt

CoRR, 2024

2023

MMTD: Multistage Moving Target Defense for Security-Enhanced D-FACTS Operation.

Jiazhou Wang, Jue Tian, Yang Liu, Dong Yang, Ting Liu

IEEE Internet Things J., July, 2023

Toward real-time automatic treatment planning (RTTP) with a one-step 3D fluence map prediction method and (nonorthogonal) convolution technique.

Jiayuan Peng, Cui Yang, Hongbo Guo, Lijun Shen, Min Zhang, Jiazhou Wang, Zhen Zhang, Bin Cai, Weigang Hu

Comput. Methods Programs Biomed., April, 2023

2022

Multi-stage Moving Target Defense: A Security-enhanced D-FACTS Implementation Approach.

Jiazhou Wang, Jue Tian, Yang Liu, Xiaohong Guan, Dong Yang, Ting Liu

CoRR, 2022

An Efficient and Robust System for Vertically Federated Random Forest.

Houpu Yao, Jiazhou Wang, Peng Dai, Liefeng Bo, Yanqing Chen

CoRR, 2022

Multimodal image translation via deep learning inference model trained in video domain.

Jiawei Fan, Zhiqiang Liu, Dong Yang, Jian Qiao, Jun Zhao, Jiazhou Wang, Weigang Hu

BMC Medical Imaging, 2022

Moving Target Defense Oriented D-FACTS Deployment and Operation.

Zhen Yu, Binger Ye, Jiazhou Wang, Yinguo Yang, Qiuyu Lu, Yu Zhu, Shuangxi Wu, Yang Liu

Proceedings of the IEEE PES Innovative Smart Grid Technologies - Asia, 2022

2021

Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform.

Bo Liu, Chaowei Tan, Jiazhou Wang, Tao Zeng, Huasong Shan, Houpu Yao, Heng Huang, Peng Dai, Liefeng Bo, Yanqing Chen

CoRR, 2021

Combining Images and T-Staging Information to Improve the Automatic Segmentation of Nasopharyngeal Carcinoma Tumors in MR Images.

Mingwei Cai, Jiazhou Wang, Qing Yang, Ying Guo, Zhen Zhang, Hongmei Ying, Weigang Hu, Chaosu Hu

IEEE Access, 2021

2017

Development of a deep neural network derived from contours defined by consensus-based guidelines for automatic target segmentation in hepatocellular carcinoma radiotherapy: A study protocol.

Jiandong Zhao, Jiazhou Wang, Mingxia Cheng

F1000Research, 2017