TA3a.2

Proximally Regularized Multitask Learning over Networks

Stefan Vlaski, Imperial College London, United Kingdom; Roula Nassif, Université Côte d’Azur, France
Session:
TA3a: Distributed Optimization and Learning Lecture
Track:
Networks and Graphs
Location:
Scripps
Presentation Time:
Tue, 29 Oct, 08:40 - 09:05 PT (UTC -8)
Session Chair:
Cesar Uribe, Rice University
Presentation
Discussion
Resources
No resources available.
Session TA3a
TA3a.1: The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity
Tongle Wu, Ying Sun, The Pennsylvania State University, United States
TA3a.2: Proximally Regularized Multitask Learning over Networks
Stefan Vlaski, Imperial College London, United Kingdom; Roula Nassif, Université Côte d’Azur, France
TA3a.3: Byzantine-Resilient Dual Methods for Vertical Federated Optimization
Jinghua Huang, Peking University, China; Zhaoxian Wu, Rensselaer Polytechnic Institute, United States; Qing Ling, Sun Yat-sen University, China; Kun Yuan, Peking University, China
TA3a.4: ADMM for Downlink Beamforming in Cell-Free Massive MIMO Systems
Mehdi Zafari, Divyanshu Pandey, Rahman Doost-Mohammady, César A. Uribe, Rice University, United States
Contacts