| Federated learning with Bayesian differential privacy A Triastcyn, B Faltings 2019 IEEE International Conference on Big Data (Big Data), 2587-2596, 2019 | 237 | 2019 |
| Generating Artificial Data for Private Deep Learning A Triastcyn, B Faltings AAAI Spring Symposium Series, 2019 | 110* | 2019 |
| Bayesian differential privacy for machine learning A Triastcyn, B Faltings International Conference on Machine Learning, 9583-9592, 2020 | 100 | 2020 |
| Federated generative privacy A Triastcyn, B Faltings IEEE Intelligent Systems, 2020 | 85 | 2020 |
| Dp-rec: Private & communication-efficient federated learning A Triastcyn, M Reisser, C Louizos arXiv preprint arXiv:2111.05454, 2021 | 17 | 2021 |
| Unsupervised information obfuscation for split inference of neural networks M Samragh, H Hosseini, A Triastcyn, K Azarian, J Soriaga, F Koushanfar arXiv preprint arXiv:2104.11413, 2021 | 15 | 2021 |
| A distributed differentially private algorithm for resource allocation in unboundedly large settings P Danassis, A Triastcyn, B Faltings arXiv preprint arXiv:2011.07934, 2020 | 9 | 2020 |
| Data-Aware Privacy-Preserving Machine Learning A Triastcyn EPFL, 2020 | 9 | 2020 |
| Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees A Triastcyn, B Faltings Algorithms 15 (7), 232, 2022 | 6 | 2022 |
| Decentralized learning with random walks and communication-efficient adaptive optimization A Triastcyn, M Reisser, C Louizos Workshop on Federated Learning: Recent Advances and New Challenges (in …, 2022 | 6 | 2022 |
| Exposing external content in an enterprise A Macksood, AN Triastcyn, K Seleskerov, VT Knudsen, P Sakkos US Patent App. 14/845,978, 2017 | 4 | 2017 |
| Differentially private multi-agent constraint optimization S Damle, A Triastcyn, B Faltings, S Gujar IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent …, 2021 | 3 | 2021 |
| Who wants to be a millionaire? H Gasimov, A Triastcyn, P Motlicek, H Bourlard Idiap, 2012 | 2 | 2012 |
| Recombinant zoster vaccine and reduced risk of dementia: matched‐cohort study using large‐scale electronic health records and machine learning methodology P Schwab, R Widenmaier, H Tahrat, M Littmann, B Anspach, ... Alzheimer's & Dementia 20, e088064, 2024 | 1 | 2024 |
| Deep learning cluster analysis reveals subtypes in response to antisense oligonucleotide therapy in chronic hepatitis B C Weis, M Littmann, A Triastcyn, W Jordan, D Theodore, M Paff, H Tipney, ... Journal of Hepatology 78, S1151-S1152, 2023 | 1 | 2023 |
| Differential Privacy Meets Maximum-weight Matching P Danassis, A Triastcyn, B Faltings CoRR, 2020 | 1 | 2020 |
| MediaEval 2012 Visual Privacy Task: Applying Transform-domain Scrambling to Automatically Detected Faces P Korshunov, A Triastcyn, T Ebrahimi CEUR Workshop Proceedings, 2012 | 1 | 2012 |
| Bi-directional compression and privacy for efficient communication in federated learning M Reisser, A Triastcyn, C Louizos US Patent App. 18/556,622, 2024 | | 2024 |
| Актуальные проблемы механики, математики, информатики АЮ Городилов, ЮН Еленский, СВ Русаков, ОЛ Русакова, ... | | 2010 |
