Bayu Anggorojati

Reliability-Aware Client Selection in Asynchronous and Heterogeneous Federated Learning

Polaris is a client selection framework for asynchronous and heterogeneous federated learning that employs quality-aware sampling to accelerate convergence. Its reliance on scalar update norms as quality indicators exposes it to exploitation, in which clients submit near-zero Gaussian updates that inflate the update ma...