Giorgio Patrini
Giorgio Patrini
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TitleCited byYear
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
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
(Almost) No Label No Cry
G Patrini, R Nock, P Rivera, T Caetano
Advances in Neural Information Processing Systems, 190-198, 2014
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
Tsallis regularized optimal transport and ecological inference
B Muzellec, R Nock, G Patrini, F Nielsen
Thirty-First AAAI Conference on Artificial Intelligence, 2017
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
Combining local search techniques and path following for bimatrix games
N Gatti, G Patrini, M Rocco, T Sandholm
arXiv preprint arXiv:1210.4858, 2012
Rademacher observations, private data, and boosting
R Nock, G Patrini, A Friedman
International Conference on Machine Learning, 948-956, 2015
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
Sinkhorn autoencoders
G Patrini, R Berg, P Forré, M Carioni, S Bhargav, M Welling, T Genewein, ...
arXiv preprint arXiv:1810.01118, 2018
Fast Learning from Distributed Datasets without Entity Matching
G Patrini, R Nock, S Hardy, T Caetano
IJCAI 2016, 2016
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
Privacy-preserving entity resolution and logistic regression on encrypted data
M Djatmiko, S Hardy, W Henecka, H Ivey-Law, M Ott, G Patrini, G Smith, ...
SEALion: a Framework for Neural Network Inference on Encrypted Data
T van Elsloo, G Patrini, H Ivey-Law
arXiv preprint arXiv:1904.12840, 2019
Weakly supervised learning via statistical sufficiency
G Patrini
The Australian National University, 2016
Bridging weak supervision and privacy aware learning via sufficient statistics
G Patrini, F Nielsen, R Nock
NIPS 2015, workshop on Learning and privacy with incomplete data and weak …, 2015
Three Tools for Practical Differential Privacy
KL van der Veen, R Seggers, P Bloem, G Patrini
arXiv preprint arXiv:1812.02890, 2018
Learning from distributed data
R Nock, G Patrini
US Patent App. 15/550,302, 2018
The state of deepfakes: reality under attack. Annual Report 2018
G Patrini, F Cavalli …, 2018
Learning with transformed data
R Nock, G Patrini, T Caetano
US Patent App. 15/521,441, 2017
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