MP6b1.4

Federated Learning for Massive MIMO Power Allocation

Yushu Yan, Xiangyu Chang, Basak Guler, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy, University of California, Riverside, United States; Ananthram Swami, Army Research Laboratory, United States
Session:
MP6b1: Federated Learning over Wireless Edge Devices II (Invited) Poster
Track:
Networks
Location:
Kiln
Presentation Time:
Mon, 30 Oct, 15:30 - 17:35 PT (UTC -8)
Session Chair:
Basak Guler, University of California, Riverside
Presentation
Discussion
Resources
No resources available.
Session MP6b1
MP6b1.1: Rethinking the Data Heterogeneity in Federated Learning
Jiayi Wang, University of Utah, United States; Shiqiang Wang, IBM T. J. Watson Research Center, United States; Rong-Rong Chen, Mingyue Ji, University of Utah, United States
MP6b1.2: Secure Summation - An Information Theoretic View
Yizhou Zhao, Zhou Li, Hua Sun, University of North Texas, United States
MP6b1.3: Differentially-Private Collaborative Online Personalized Mean Estimation
Yauhen Yakimenka, New Jersey Institute of Technology, United States; Chung-Wei Weng, Hsuan-Yin Lin, Eirik Rosnes, Simula UiB, Norway; Joerg Kliewer, New Jersey Institute of Technology, United States
MP6b1.4: Federated Learning for Massive MIMO Power Allocation
Yushu Yan, Xiangyu Chang, Basak Guler, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy, University of California, Riverside, United States; Ananthram Swami, Army Research Laboratory, United States
Contacts