SPCOM-P1.4
SemDA: Communication-efficient Data Aggregation Through Distributed Semantic Transmission
Yaru Zhao, Yakun Huang, Beijing University of Posts and Telecommunications, China
Session:
SPCOM-P1: Distributed Processing and Federated Learning Poster
Track:
Signal Processing for Communications and Networking
Location:
Poster Zone 4A
Poster Board PZ-4A.4
Poster Board PZ-4A.4
Presentation Time:
Tue, 16 Apr, 13:10 - 15:10 (UTC +9)
Session Chair:
Jun Zhang, Hong Kong University of Science and Technology
Session SPCOM-P1
SPCOM-P1.1: DECENTRALIZING COHERENT JOINT TRANSMISSION PRECODING VIA DETERMINISTIC EQUIVALENTS
Yuhao Liu, Tsinghua University, China; Xinyu Bian, The Hong Kong University of Science and Technology, Hong Kong; Yizhou Xu, Tsinghua University, China; Tianqi Hou, Wenjie Wang, Huawei Technologies Co., Ltd, China; Yuyi Mao, The Hong Kong Polytechnic University, Hong Kong; Jun Zhang, The Hong Kong University of Science and Technology, Hong Kong
SPCOM-P1.2: UTILIZING SECOND-ORDER INFORMATION IN NOISY INFORMATION-SHARING ENVIRONMENTS FOR DISTRIBUTED OPTIMIZATION
Zhaoye Pan, Haoqi Yang, Huikang Liu, Shanghai University of Finance and Economics, China
SPCOM-P1.3: Scaling Results for Robust Distributed Estimation in Sensor Networks using Order Statistics
Umar Rashid, Rafay Chughtai, University of Engineering & Technology, Lahore, Pakistan
SPCOM-P1.4: SemDA: Communication-efficient Data Aggregation Through Distributed Semantic Transmission
Yaru Zhao, Yakun Huang, Beijing University of Posts and Telecommunications, China
SPCOM-P1.5: ENERGY EFFICIENT WAKE-UP SOLUTION FOR LARGE-SCALE INTERNET OF UNDERWATER THINGS NETWORKS
Abdulaziz Al-Amodi, King Fahd University of Petroleum and Minerals, Saudi Arabia; Nour Kouzayha, King Abdullah University of Science and Technology, Saudi Arabia; Nasir Saeed, United Arab Emirates University, United Arab Emirates; Mudassir Masood, King Fahd University of Petroleum and Minerals, Saudi Arabia; Tareq Al-Naffouri, King Abdullah University of Science and Technology, Saudi Arabia
SPCOM-P1.6: Friends to Help: Saving Federated Learning from Client Dropout
Heqiang Wang, Jie Xu, University of Miami, United States of America
SPCOM-P1.7: META-KNOWLEDGE ENHANCED DATA AUGMENTATION FOR FEDERATED PERSON RE-IDENTIFICATION
Chunli Song, Hunan University of Technology, China; Xiaohua Chen, Institute of Information Engineering, Chinese Academy of Sciences, China; Wenqiu Zhu, Hunan University of Technology, China; Yucan Zhou, Xiaoyan Gu, Bo Li, Institute of Information Engineering, Chinese Academy of Sciences, China
SPCOM-P1.8: EFFICIENT FEDERATED LEARNING WITH SMOOTH AGGREGATION FOR NON-IID DATA FROM MULTIPLE EDGES
Qianru Wang, Qingyang Li, Xidian University, China; Bin Guo, Northwestern Polytechnical University, China; Jiangtao Cui, Xidian University, China
SPCOM-P1.9: ON THE RESILIENCE OF ONLINE FEDERATED LEARNING TO MODEL POISONING ATTACKS THROUGH PARTIAL SHARING
Ehsan Lari, Norwegian University of Science and Technology, Norway; Vinay Chakravarthi Gogineni, University of Southern Denmark, Denmark; Reza Arablouei, The Commonwealth Scientific and Industrial Research Organisation, Australia; Stefan Werner, Norwegian University of Science and Technology, Norway
SPCOM-P1.10: FED-SDS: ADAPTIVE STRUCTURED DYNAMIC SPARSITY FOR FEDERATED LEARNING UNDER HETEROGENEOUS CLIENTS
Yujun Cheng, Zhewei Zhang, Shengjin Wang, Tsinghua University, China
Contacts