most citedFedFm: Towards a Robust Federated Learning Approach For Fault Mitigation at the Edge Nodes

8 citations · 8 across the 2 of their papers we have counts for

collaborators

2 papers

cs.IT2022

Secure and Ultra-Reliable Provenance Recovery in Sparse Networks: Strategies and Performance Bounds

Suraj Sajeev, Manish Bansal, Sriraam S +3

Provenance embedding algorithms are well known for tracking the footprints of information flow in wireless networks. Recently, low-latency provenance embedding algorithms have rece…

cs.LG2021★ 8 cited

FedFm: Towards a Robust Federated Learning Approach For Fault Mitigation at the Edge Nodes

Manupriya Gupta, Pavas Goyal, Rohit Verma +2

Federated Learning deviates from the norm of "send data to model" to "send model to data". When used in an edge ecosystem, numerous heterogeneous edge devices collecting data throu…