no code implementations • 15 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.
no code implementations • 17 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.
no code implementations • 16 Feb 2021 • Matthias Paulik, Matt Seigel, Henry Mason, Dominic Telaar, Joris Kluivers, Rogier Van Dalen, Chi Wai Lau, Luke Carlson, Filip Granqvist, Chris Vandevelde, Sudeep Agarwal, Julien Freudiger, Andrew Byde, Abhishek Bhowmick, Gaurav Kapoor, Si Beaumont, Áine Cahill, Dominic Hughes, Omid Javidbakht, Fei Dong, Rehan Rishi, Stanley Hung
We describe the design of our federated task processing system.
no code implementations • 6 Aug 2020 • Filip Granqvist, Matt Seigel, Rogier Van Dalen, Áine Cahill, Stephen Shum, Matthias Paulik
From these features, the model predicts speaker characteristic labels considered useful as side information.