Search Results for author: Matt Seigel

Found 4 papers, 0 papers with code

Training a Tokenizer for Free with Private Federated Learning

no code implementations15 Mar 2022 Eugene Bagdasaryan, Congzheng Song, Rogier Van Dalen, Matt Seigel, Áine Cahill

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 Learning Language Modelling

Enforcing fairness in private federated learning via the modified method of differential multipliers

no code implementations17 Sep 2021 Borja Rodríguez-Gálvez, Filip Granqvist, Rogier Van Dalen, Matt Seigel

This paper introduces an algorithm to enforce group fairness in private federated learning, where users' data does not leave their devices.

BIG-bench Machine Learning Fairness +1

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