TH1.AUD.6
Learned Finite-Time Consensus for Distributed Optimization
Aaron Fainman, Stefan Vlaski, Imperial College London, United Kingdom
Session:
TH1.AUD: From Distributed to Federated Learning over Networks Lecture
Track:
Special Sessions
Location:
Auditorium
Presentation Time:
Thu, 29 Aug, 12:10 - 12:30 France Time (UTC +1)
Session Chair:
Cedric Richard, Universite Cote d’Azur
Presentation
Discussion
Resources
No resources available.
Session TH1.AUD
TH1.AUD.1: PRIVACY-PRESERVING DISTRIBUTED NONNEGATIVE MATRIX FACTORIZATION
Ehsan Lari, Norwegian University of Science and Technology, Norway; Reza Arablouei, Commonwealth Scientific and Industrial Research Organisation, Australia; Stefan Werner, Norwegian University of Science and Technology, Norway
TH1.AUD.2: Analysis of Total Variation Minimization for Clustered Federated Learning
Alexander Jung, Aalto University, Finland
TH1.AUD.3: ADAPTIVE SOCIAL LEARNING FOR TRACKING RARE TRANSITION MARKOV CHAINS
Malek Khammassi, Virginia Bordignon, EPFL, Switzerland; Vincenzo Matta, University of Salerno, Italy; Ali H. Sayed, EPFL, Switzerland
TH1.AUD.4: Communication-efficient Vertical Federated Learning via Compressed Error Feedback
Pedro Valdeira, Carnegie Mellon University & Universidade de Lisboa, Portugal; João Xavier, Universidade de Lisboa, Portugal; Cláudia Soares, Universidade Nova de Lisboa, Portugal; Yuejie Chi, Carnegie Mellon University, United States
TH1.AUD.5: Online Parameter Estimation Over Distributed Multitask Networks With A Rank-one Model
Yitong Chen, School of Marine Science and Technolgy, Northwestern Polytechnical University, China; Danqi Jin, School of Electronic Information, Wuhan University, China; Jie Chen, School of Marine Science and Technolgy, Northwestern Polytechnical University, China; Cedric Richard, Universite Cote d’Azur, France; Wen Zhang, School of Marine Science and Technolgy, Northwestern Polytechnical University, China; Gongping Huang, School of Electronic Information, Wuhan University, China; Jingdong Chen, School of Marine Science and Technolgy, Northwestern Polytechnical University, China
TH1.AUD.6: Learned Finite-Time Consensus for Distributed Optimization
Aaron Fainman, Stefan Vlaski, Imperial College London, United Kingdom