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Filip Granqvist
Filip Granqvist
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Title
Cited by
Cited by
Year
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
1052021
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
652020
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
302021
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
252021
Flair: Federated learning annotated image repository
C Song, F Granqvist, K Talwar
Advances in Neural Information Processing Systems 35, 37792-37805, 2022
242022
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
212023
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
82023
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
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Articles 1–10