4 papers · 1 filter
Hierarchical Federated Learning with Multi-Timescale Gradient Correction
Wenzhi Fang, Dong-Jun Han, Evan Chen +2
While traditional federated learning (FL) typically focuses on a star topology where clients are directly connected to a central server, real-world distributed systems often exhibi…
A Hierarchical Gradient Tracking Algorithm for Mitigating Subnet-Drift in Fog Learning Networks
Evan Chen, Shiqiang Wang, Christopher G. Brinton
Federated learning (FL) encounters scalability challenges when implemented over fog networks that do not follow FL's conventional star topology architecture. Semi-decentralized FL…
Taming Subnet-Drift in D2D-Enabled Fog Learning: A Hierarchical Gradient Tracking Approach
Evan Chen, Shiqiang Wang, Christopher G. Brinton
Federated learning (FL) encounters scalability challenges when implemented over fog networks. Semi-decentralized FL (SD-FL) proposes a solution that divides model cooperation into…
Differentially-Private Multi-Tier Federated Learning
Evan Chen, Frank Po-Chen Lin, Dong-Jun Han +1
While federated learning (FL) eliminates the transmission of raw data over a network, it is still vulnerable to privacy breaches from the communicated model parameters. In this wor…