To handle these problems, this paper proposes a data fitting based weight compression algorithm, FWC, which includes four sequential stages: sparsification, ...

A data fitting based weight compression algorithm, FWC, which includes four sequential stages: sparsification, polynomial fitting, encoding, ...

1) We propose a fitting weight compression algorithm. FWC for federated learning. Inheriting all the ad- vantages of FedAVG, our FWC provides a more.

Ribero introduced the Ornstein-Uhlenbeck [16] process to select a subset of clients with significant weight updates, greatly reducing communication overhead.

This paper shows that the dynamic and orthogonal AE based weight compression technique could serve as an advantageous alternative (or an add-on) in a large ...

We investigate energy-efficient federated learning (FL) in computation and communication resource-constrained edge intelligence networks using model compression ...

FWC: Fitting Weight Compression Method for Reducing Communication Traffic for Federated Learning ... fitting based weight compression algorithm, FWC, which ...

FWC: Fitting Weight Compression Method for Reducing Communication Traffic for Federated Learning ... TL;DR: Wang et al. as mentioned in this paper proposed a data ...

Missing: FWC: Fitting Traffic

FedAT: A Communication-Efficient Federated Learning Method ... FWC: Fitting Weight Compression Method for Reducing Communication Traffic for Federated Learning.