FEDZIP: A Compression Framework for Communication-Efficient Federated Learning

Understand

Federated Learning marks a turning point in the implementation of decentralized machine learning (especially deep learning) for wireless devices by protecting users' privacy and safeguarding raw data from third-party access.

• It assigns the learning process independently to each client.
• First, clients locally train a machine learning model based on local data.
• Next, clients transfer local updates of model weights and biases (training data) to a server.