Technical Program

L.5: Federated Learning

Session Type: Lecture
Track: Statistics and Learning Theory
Virtual Session: View on Virtual Platform
Session Chair: Changho Suh, Korea Advanced Institute of Science and Technology
 
L.5.1: Federated Recommendation System via Differential Privacy
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         Tan Li; City University of Hong Kong
         Linqi Song; City University of Hong Kong
         Christina Fragouli; University of California, Los Angeles
 
L.5.2: Update Aware Device Scheduling for Federated Learning at the Wireless Edge
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         Mohammad Mohammadi Amiri; Princeton University
         Deniz Gunduz; Imperial College London
         Sanjeev R. Kulkarni; Princeton University
         H. Vincent Poor; Princeton University
 
L.5.3: Wireless Federated Learning with Local Differential Privacy
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         Mohamed Seif; University of Arizona
         Ravi Tandon; University of Arizona
         Ming Li; University of Arizona
 
L.5.4: The Communication-Aware Clustered Federated Learning Problem
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         Nir Shlezinger; Weizmann Institute of Science
         Stefano Rini; National Chiao Tung University
         Yonina Eldar; Weizmann Institute of Science
 

Plan Ahead

IEEE ISIT 2021

2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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