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Found 4 papers, 1 papers with code
pfl-research: simulation framework for accelerating research in Private Federated Learning
Federated learning (FL) is an emerging machine learning (ML) training paradigm where clients own their data and collaborate to train a global model, without revealing any data to the server and other participants.
Training a Tokenizer for Free with Private Federated Learning
During private federated learning of the language model, we sample from the model, train a new tokenizer on the sampled sequences, and update the model embeddings.
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
We describe the design of our federated task processing system.
Improving on-device speaker verification using federated learning with privacy
From these features, the model predicts speaker characteristic labels considered useful as side information.
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