Scalable and Resource-Efficient Second-Order Federated Learning via Over-the-Air Aggregation
Second-order federated learning (FL) algorithms offer faster convergence than their first-order counterparts by leveraging curvature information. However, they are hindered by high […]
Quantized FedPD (QFedPD): Beyond Conventional Wisdom – The Energy Benefits of Frequent Communication
Federated Averaging (FedAvg) is a well-recognized framework for distributed learning that efficiently manages communication. Several algorithms have emerged to enhance the communication […]
On the Primal Feasibility in Dual Decomposition Methods Under Additive and Bounded Errors
With the unprecedented growth of signal processing and machine learning application domains, there has been a tremendous expansion of interest in distributed […]