Improving On-Device Speaker Verification Using Federated Learning with Privacy. - Filip Granqvist; Matt Seigel; Rogier C. van Dalen; Áine Cahill; Stephen Shum; Matthias Paulik (INTERSPEECH, 2020)

Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications. - Matthias Paulik; Matt Seigel; Henry Mason; Dominic Telaar; Joris Kluivers; Rogier C. van Dalen; Chi Wai Lau; Luke Carlson; Filip Granqvist; Chris Vandevelde; Sudeep Agarwal; Julien Freudiger; et al. (CoRR, 2021)

Enforcing fairness in private federated learning via the modified method of differential multipliers. - Borja Rodríguez Gálvez; Filip Granqvist; Rogier C. van Dalen; Matt Seigel (CoRR, 2021)

FLAIR: Federated Learning Annotated Image Repository. - Congzheng Song; Filip Granqvist; Kunal Talwar (NeurIPS, 2022)

Training Large-Vocabulary Neural Language Models by Private Federated Learning for Resource-Constrained Devices. - Mingbin Xu; Congzheng Song; Ye Tian; Neha Agrawal; Filip Granqvist; Rogier C. van Dalen; Xiao Zhang; Arturo Argueta; Shiyi Han; Yaqiao Deng; Leo Liu; Anmol Walia; et al. (ICASSP, 2023)

Samplable Anonymous Aggregation for Private Federated Data Analysis. - Kunal Talwar; Shan Wang; Audra McMillan; Vojta Jina; Vitaly Feldman; Bailey Basile; Áine Cahill; Yi Sheng Chan; Mike Chatzidakis; Junye Chen; Oliver R. A. Chick; Mona Chitnis; et al. (CoRR, 2023)

Samplable Anonymous Aggregation for Private Federated Data Analysis. - Kunal Talwar; Shan Wang; Audra McMillan; Vitaly Feldman; Pansy Bansal; Bailey Basile; Áine Cahill; Yi Sheng Chan; Mike Chatzidakis; Junye Chen; Oliver R. A. Chick; Mona Chitnis; et al. (CCS, 2024)

pfl-research: simulation framework for accelerating research in Private Federated Learning. - Filip Granqvist; Congzheng Song; Áine Cahill; Rogier C. van Dalen; Martin Pelikan; Yi Sheng Chan; Xiaojun Feng; Natarajan Krishnaswami; Vojta Jina; Mona Chitnis (NeurIPS, 2024)