MA6a2.4

Achieving Joint Privacy and Communication Efficiency in Federated Learning and Analytics

Wei-Ning Chen, Ayfer Ozgur, Stanford University, United States
Session:
MA6a2: Federated Learning over Wireless Edge Devices I (Invited) Poster
Track:
Communications Systems
Location:
Kiln
Presentation Time:
Mon, 30 Oct, 08:15 - 09:55 PT (UTC -8)
Session Chair:
Mingzhe Chen, University of Miami
Presentation
Discussion
Resources
No resources available.
Session MA6a2
MA6a2.1: On the Tradeoff Between Heterogeneity and Communication Complexity in Federated Learning
Priyanka Sinha, Jacek Kibilda, Walid Saad, Virginia Tech, United States
MA6a2.2: Complex Neural Network based Federated learning for Radio Frequency based Positioning
Mingzhe Chen, University of Miami, United States
MA6a2.3: Multi-task Federated Learning for Radio Access Networks
Hasan Farooq, Ericsson, United States
MA6a2.4: Achieving Joint Privacy and Communication Efficiency in Federated Learning and Analytics
Wei-Ning Chen, Ayfer Ozgur, Stanford University, United States
Contacts