1 citations · 1 across the 8 of their papers we have counts for
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Towards Serverless Semi-Decentralized Federated Learning with Heterogeneous Optimizers
Su Wang, Mung Chiang, H. Vincent Poor
We investigate cluster formation, involving the number and composition of clusters, in decentralized federated learning (FL) with heterogeneous machine learning (ML) optimizers. Wh…
Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels
Md Kamran Chowdhury Shisher, Vishrant Tripathi, Mung Chiang +1
The restless multi-armed bandit (RMAB) framework is a popular approach to solving resource allocation problems in networked systems. In this paper, we study optimal resource alloca…
Communication-Efficient Federated Learning under Dynamic Device Arrival and Departure: Convergence Analysis and Algorithm Design
Zhan-Lun Chang, Dong-Jun Han, Seyyedali Hosseinalipour +2
Most federated learning (FL) approaches assume a fixed device set. However, real-world scenarios often involve devices dynamically joining or leaving the system, driven by, e.g., u…