73 citations · 84 across the 9 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
cs.LG2020★ 73 cited
Training Speech Recognition Models with Federated Learning: A Quality/Cost Framework
Dhruv Guliani, Francoise Beaufays, Giovanni Motta
We propose using federated learning, a decentralized on-device learning paradigm, to train speech recognition models. By performing epochs of training on a per-user basis, federate…
eess.AS2020
Low-rank Gradient Approximation For Memory-Efficient On-device Training of Deep Neural Network
Mary Gooneratne, Khe Chai Sim, Petr Zadrazil +3
Training machine learning models on mobile devices has the potential of improving both privacy and accuracy of the models. However, one of the major obstacles to achieving this goa…