127 citations · 461 across the 65 of their papers we have counts for
5 papers · 2 filters
Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading
Dong-Jun Han, Seyyedali Hosseinalipour, David J. Love +2
While network coverage maps continue to expand, many devices located in remote areas remain unconnected to terrestrial communication infrastructures, preventing them from getting a…
Multi-Source to Multi-Target Decentralized Federated Domain Adaptation
Su Wang, Seyyedali Hosseinalipour, Christopher G. Brinton
Heterogeneity across devices in federated learning (FL) typically refers to statistical (e.g., non-i.i.d. data distributions) and resource (e.g., communication bandwidth) dimension…
Distributed Linear Solvers and Data Heterogeneity
Boris Velasevic, Rohit Parasnis, Christopher G. Brinton +1
We consider the problem of solving a large-scale system of linear equations in a distributed/federated setting. The taskmaster solves the system with the help of a set of machines,…
Towards Cooperative Federated Learning over Heterogeneous Edge/Fog Networks
Su Wang, Seyyedali Hosseinalipour, Vaneet Aggarwal +4
Federated learning (FL) has been promoted as a popular technique for training machine learning (ML) models over edge/fog networks. Traditional implementations of FL have largely ne…
Connectivity-Aware Semi-Decentralized Federated Learning over Time-Varying D2D Networks
Rohit Parasnis, Seyyedali Hosseinalipour, Yun-Wei Chu +2
Semi-decentralized federated learning blends the conventional device to-server (D2S) interaction structure of federated model training with localized device-to-device (D2D) communi…