MLSP-L5.3

DUAL-CHANNEL PERSONALIZED FEDERATED BUNDLE RECOMMENDATION

Linrui Shen, Anchen Li, Xueyan Liu, Jilin University, China; Riting Xia, Inner Mongolia University, China; Bo Yang, Jilin University, China
Session:
MLSP-L5: Distributed Federated Learning Systems and Algorithms Oral
Track:
Machine Learning for Signal Processing [ML]
Location:
Room 113
Presentation Time:
Tue, 5 May, 17:10 - 17:30
Presentation
Discussion
Resources
No resources available.
Session MLSP-L5
MLSP-L5.1: Collusion-Resistant and Trusted Authority-Free Verifiable Federated Learning via a Two-Server Architecture
Haofei Wang, Li-Ping Wang, State Key Laboratory of Cyberspace Security Defense, Institute of Information Engineering, CAS, University of Chinese Academy of Sciences, China; Liang Feng Zhang, ShanghaiTech University, China; Huaxiong Wang, Nanyang Technological University, Singapore
MLSP-L5.2: FedSKU: Defending Backdoors in Federated Learning Through Selective Knowledge Unlearning
Guofu Xie, Remin University of China, China; Yu Zhou, Bingyan Liu, Beijing University of Posts and Telecommunications, China
MLSP-L5.3: DUAL-CHANNEL PERSONALIZED FEDERATED BUNDLE RECOMMENDATION
Linrui Shen, Anchen Li, Xueyan Liu, Jilin University, China; Riting Xia, Inner Mongolia University, China; Bo Yang, Jilin University, China
MLSP-L5.4: COOPERATIVE MULTI-AGENT REINFORCEMENT LEARNING FOR ADAPTIVE AGGREGATION IN SEMI-SUPERVISED FEDERATED LEARNING WITH NON-IID DATA
Rene Glitza, Luca Becker, Rainer Martin, Ruhr-Universität Bochum, Germany
MLSP-L5.5: COSAGE: FEDERATED LEARNING WITH GRADIENT SUMMARIES FOR CENTRALIZED CLIENT SELECTION
Houman Asgari, Technical University of Munich, Germany; Stefano Rini, National Yang Ming Chiao Tung University, Taiwan; Andrea Munari, German Aerospace Center (DLR), Germany
MLSP-L5.6: Channel-Adaptive Robust Aggregation for Over-the-Air Federated Learning in Heterogeneous Networks
Zubaida Fatima, Zubair Shaban, Yusuf Jamal, Nazreen Shah, Ranjitha Prasad, IIIT Delhi, India; B. N. Bharath, IIT Dharwad, India
Contacts