MP6b2.4

Time-Varying Noise Perturbation and Power Control for Differential-Privacy-Preserving Wireless Federated Learning

Dang Qua Nguyen, Taejoon Kim, University of Kansas, United States
Session:
MP6b2: Machine Learning for Communication Systems (Invited) Poster
Track:
Networks
Location:
Kiln
Presentation Time:
Mon, 30 Oct, 15:30 - 17:35 PT (UTC -8)
Session Chair:
Cong Shen, University of Virginia
Presentation
Discussion
Resources
No resources available.
Session MP6b2
MP6b2.1: Edge-Alloc: Mobility Focused Multi-Armed Bandit for Edge Computing
Taejin Kim, Carnegie Mellon University, United States; Jinhang Zuo, University of Massachusetts Amherst/California Institute of Technology, United States; Carlee Joe-Wong, Carnegie Mellon University, United States
MP6b2.2: Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets
Kun Yang, Cong Shen, Univeristy of Virginia, United States; Jing Yang, The Pennsylvania State University, United States; Shu-ping Yeh, Jerry Sydir, Intel Corporation, United States
MP6b2.3: Open RAN LSTM Traffic Prediction and Slice Management using Deep Reinforcement Learning
Fatemeh Lotfi, Fatemeh Afghah, Clemson University, United States
MP6b2.4: Time-Varying Noise Perturbation and Power Control for Differential-Privacy-Preserving Wireless Federated Learning
Dang Qua Nguyen, Taejoon Kim, University of Kansas, United States
Contacts