MLSP-L14: Distributed and Federated Learning I
Thu, 18 Apr, 08:20 - 10:20 (UTC +9)
Location: Room E3
Session Type: Lecture
Session Co-Chairs: Han Yu, Nanyang Technological University and Sheng Li, National Institute of Information and Communications Technology (NICT) Japan
Track: Machine Learning for Signal Processing
Click the to view the manuscript on IEEE Xplore Open Preview
Thu, 18 Apr, 08:20 - 08:40 (UTC +9)
 

MLSP-L14.1: UNIDEAL: CURRICULUM KNOWLEDGE DISTILLATION FEDERATED LEARNING
Yuwen Yang, Chang Liu, Xun Cai, Suizhi Huang, Hongtao Lu, Yue Ding, Shanghai Jiao Tong University, China
Thu, 18 Apr, 08:40 - 09:00 (UTC +9)
 

MLSP-L14.2: FEDERATED CINN CLUSTERING FOR ACCURATE CLUSTERED FEDERATED LEARNING
Yuhao Zhou, Minjia Shi, Yuxin Tian, Sichuan University, China; Yuanxi Li, University of Illinois at Urbana-Champaign, United States of America; Qing Ye, Jiancheng Lv, Sichuan University, China
Thu, 18 Apr, 09:00 - 09:20 (UTC +9)
 

MLSP-L14.3: FAIRNESS-AWARE JOB SCHEDULING FOR MULTI-JOB FEDERATED LEARNING
Yuxin Shi, Han Yu, Nanyang Technological University, Singapore
Thu, 18 Apr, 09:20 - 09:40 (UTC +9)
 

MLSP-L14.4: Personalized Federated Learning with Attention-based Client Selection
Zihan Chen, Jundong Li, Cong Shen, University of Virginia, United States of America
Thu, 18 Apr, 09:40 - 10:00 (UTC +9)
 

MLSP-L14.5: IMPORTANCE SAMPLING BASED FEDERATED UNSUPERVISED REPRESENTATION LEARNING
Nazreen Shah, Prachi Goyal, Ranjitha Prasad, IIIT Delhi, India
Thu, 18 Apr, 10:00 - 10:20 (UTC +9)
 

MLSP-L14.6: Communication Efficient Private Federated Learning Using Dithering
Burak Hasircioglu, Deniz Gündüz, Imperial College London, United Kingdom of Great Britain and Northern Ireland