Federated evaluation and tuning for on-device personalization: System design & applications M Paulik, M Seigel, H Mason, D Telaar, J Kluivers, R van Dalen, CW Lau, ... arXiv preprint arXiv:2102.08503, 2021 | 105 | 2021 |
Improving on-device speaker verification using federated learning with privacy F Granqvist, M Seigel, R Van Dalen, A Cahill, S Shum, M Paulik arXiv preprint arXiv:2008.02651, 2020 | 65 | 2020 |
Enforcing fairness in private federated learning via the modified method of differential multipliers BR Gálvez, F Granqvist, R van Dalen, M Seigel NeurIPS 2021 Workshop Privacy in Machine Learning, 2021 | 30 | 2021 |
Enforcing fairness in private federated learning via the modified method of differential multipliers B Rodríguez-Gálvez, F Granqvist, R van Dalen, M Seigel arXiv preprint arXiv:2109.08604, 2021 | 25 | 2021 |
Flair: Federated learning annotated image repository C Song, F Granqvist, K Talwar Advances in Neural Information Processing Systems 35, 37792-37805, 2022 | 24 | 2022 |
Training large-vocabulary neural language models by private federated learning for resource-constrained devices M Xu, C Song, Y Tian, N Agrawal, F Granqvist, R van Dalen, X Zhang, ... ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 21 | 2023 |
Samplable anonymous aggregation for private federated data analysis K Talwar, S Wang, A McMillan, V Jina, V Feldman, P Bansal, B Basile, ... arXiv preprint arXiv:2307.15017, 2023 | 8 | 2023 |
pfl-research: simulation framework for accelerating research in Private Federated Learning F Granqvist, C Song, Á Cahill, R van Dalen, M Pelikan, YS Chan, X Feng, ... arXiv preprint arXiv:2404.06430, 2024 | | 2024 |
A deep learning based tracking framework for passenger monitoring F Granqvist, O Holmberg | | 2018 |
Virtual Reality Car Driving Simulator AR Gustavsson, F Granqvist, J Bengtsson, M Engelke, R Lorentzon, ... | | 2016 |