Making deep neural networks robust to label noise: a loss correction approach G Patrini, A Rozza, A Menon, R Nock, L Qu arXiv preprint arXiv:1609.03683, 2016 | 1605 | 2016 |
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption S Hardy, W Henecka, H Ivey-Law, R Nock, G Patrini, G Smith, B Thorne arXiv preprint arXiv:1711.10677, 2017 | 623 | 2017 |
The State Of Deepfakes: Landscape, Threats and Impact H Ajder, G Patrini, F Cavalli, L Cullen https://sensity.ai/reports, 2019 | 223 | 2019 |
Loss factorization, weakly supervised learning and label noise robustness G Patrini, F Nielsen, R Nock, M Carioni International conference on machine learning, 708-717, 2016 | 133 | 2016 |
Sinkhorn autoencoders G Patrini, R Van den Berg, P Forre, M Carioni, S Bhargav, M Welling, ... Uncertainty in Artificial Intelligence, 733-743, 2020 | 112 | 2020 |
Entity resolution and federated learning get a federated resolution R Nock, S Hardy, W Henecka, H Ivey-Law, G Patrini, G Smith, B Thorne arXiv preprint arXiv:1803.04035, 2018 | 108 | 2018 |
Tsallis regularized optimal transport and ecological inference B Muzellec, R Nock, G Patrini, F Nielsen Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 58 | 2017 |
SEALion: A framework for neural network inference on encrypted data T van Elsloo, G Patrini, H Ivey-Law arXiv preprint arXiv:1904.12840, 2019 | 49 | 2019 |
Learning with transformed data R Nock, G Patrini, T Caetano US Patent 11,521,106, 2022 | 44 | 2022 |
Three tools for practical differential privacy KL van der Veen, R Seggers, P Bloem, G Patrini arXiv preprint arXiv:1812.02890, 2018 | 33 | 2018 |
(Almost) No Label No Cry G Patrini, R Nock, P Rivera, T Caetano Advances in Neural Information Processing Systems, 190-198, 2014 | 24 | 2014 |
The State of Deepfakes: Reality Under Attack G Patrini, F Cavalli https://s3.eu-west-2.amazonaws.com/rep2018/2018-the-state-of-deepfakes.pdf …, 2018 | 17 | 2018 |
Combining local search techniques and path following for bimatrix games N Gatti, G Patrini, M Rocco, T Sandholm arXiv preprint arXiv:1210.4858, 2012 | 17 | 2012 |
Local search methods for finding a Nash equilibrium in two-player games S Ceppi, N Gatti, G Patrini, M Rocco IAT, Toronto, Canada, 335-342, 2010 | 17 | 2010 |
Local search techniques for computing equilibria in two-player general-sum strategic-form games S Ceppi, N Gatti, G Patrini, M Rocco Proceedings of the 9th International Conference on Autonomous Agents and …, 2010 | 17 | 2010 |
Automating image abuse: deepfake bots on telegram H Ajder, G Patrini, F Cavalli Sensity, October, 2020 | 16 | 2020 |
Learning from distributed data R Nock, G Patrini US Patent 11,238,364, 2022 | 11 | 2022 |
Rademacher observations, private data, and boosting R Nock, G Patrini, A Friedman International Conference on Machine Learning, 948-956, 2015 | 11 | 2015 |
Fast Learning from Distributed Datasets without Entity Matching G Patrini, R Nock, S Hardy, T Caetano IJCAI 2016, 2016 | 10 | 2016 |
The impact of record linkage on learning from feature partitioned data R Nock, S Hardy, W Henecka, H Ivey-Law, J Nabaglo, G Patrini, G Smith, ... International Conference on Machine Learning, 8216-8226, 2021 | 9 | 2021 |