1 code implementation • 9 Apr 2024 • Filip Granqvist, Congzheng Song, Áine Cahill, Rogier Van Dalen, Martin Pelikan, Yi Sheng Chan, Xiaojun Feng, Natarajan Krishnaswami, Vojta Jina, Mona Chitnis
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.
no code implementations • 20 Jul 2023 • Rogier Van Dalen
Instead, this paper proposes to approximate the loss function, allowing global normalisation to apply to a state-of-the-art streaming model.
1 code implementation • 12 Jul 2023 • Titouan Parcollet, Rogier Van Dalen, Shucong Zhang, Sourav Bhattacharya
Unfortunately, token mixing with self-attention takes quadratic time in the length of the speech utterance, slowing down inference as well as training and increasing memory consumption.
no code implementations • 18 Jul 2022 • MingBin Xu, Congzheng Song, Ye Tian, Neha Agrawal, Filip Granqvist, Rogier Van Dalen, Xiao Zhang, Arturo Argueta, Shiyi Han, Yaqiao Deng, Leo Liu, Anmol Walia, Alex Jin
Our goal is to train a large neural network language model (NNLM) on compute-constrained devices while preserving privacy using FL and DP.
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.