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Conference and Workshop Papers
- 2024
[c3]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, Suman Ganta, Yusuf Goren, Filip Granqvist, Kristine Guo, Frederic Jacobs, Omid Javidbakht, Albert Liu, Richard Low, Dan Mascenik, Steve Myers, David Park, Wonhee Park, Gianni Parsa, Tommy Pauly, Christian Priebe, Rehan Rishi, Guy N. Rothblum, Congzheng Song, Linmao Song, Karl Tarbe, Sebastian Vogt, Shundong Zhou, Vojta Jina, Michael Scaria, Luke Winstrom:
Samplable Anonymous Aggregation for Private Federated Data Analysis. CCS 2024: 2859-2873- [c2]Jonathan Scott, Áine Cahill:
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials. ICML 2024 - 2020
- [c1]Filip Granqvist, Matt Seigel, Rogier C. van Dalen, Áine Cahill, Stephen Shum, Matthias Paulik:
Improving On-Device Speaker Verification Using Federated Learning with Privacy. INTERSPEECH 2020: 4328-4332
Informal and Other Publications
- 2024
- [i6]Filip Granqvist, Congzheng Song, Áine Cahill, Rogier C. van Dalen, Martin Pelikan, Yi Sheng Chan, Xiaojun Feng, Natarajan Krishnaswami, Vojta Jina, Mona Chitnis:
pfl-research: simulation framework for accelerating research in Private Federated Learning. CoRR abs/2404.06430 (2024) - [i5]Jonathan Scott, Áine Cahill:
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials. CoRR abs/2406.02416 (2024) - 2023
- [i4]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, Suman Ganta, Yusuf Goren, Filip Granqvist, Kristine Guo, Frederic Jacobs, Omid Javidbakht, Albert Liu, Richard Low, Dan Mascenik, Steve Myers, David Park, Wonhee Park, Gianni Parsa, Tommy Pauly, Christian Priebe, Rehan Rishi, Guy N. Rothblum, Michael Scaria, Linmao Song, Congzheng Song, Karl Tarbe, Sebastian Vogt, Luke Winstrom, Shundong Zhou:
Samplable Anonymous Aggregation for Private Federated Data Analysis. CoRR abs/2307.15017 (2023) - 2022
- [i3]Eugene Bagdasaryan, Congzheng Song, Rogier C. van Dalen, Matt Seigel, Áine Cahill:
Training a Tokenizer for Free with Private Federated Learning. CoRR abs/2203.09943 (2022) - 2021
- [i2]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, Andrew Byde, Abhishek Bhowmick, Gaurav Kapoor, Si Beaumont, Áine Cahill, Dominic Hughes, Omid Javidbakht, Fei Dong, Rehan Rishi, Stanley Hung:
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications. CoRR abs/2102.08503 (2021) - 2020
- [i1]Filip Granqvist, Matt Seigel, Rogier C. van Dalen, Áine Cahill, Stephen Shum, Matthias Paulik:
Improving on-device speaker verification using federated learning with privacy. CoRR abs/2008.02651 (2020)
Coauthor Index
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