Local search techniques for computing equilibria in two-player general-sum strategic-form games. - Sofia Ceppi; Nicola Gatti 001; Giorgio Patrini; Marco Rocco (AAMAS, 2010)

Local Search Methods for Finding a Nash Equilibrium in Two-Player Games. - Sofia Ceppi; Nicola Gatti 001; Giorgio Patrini; Marco Rocco (IAT, 2010)

Combining local search techniques and path following for bimatrix games. - Nicola Gatti 001; Giorgio Patrini; Marco Rocco; Tuomas Sandholm (UAI, 2012)

(Almost) No Label No Cry. - Giorgio Patrini; Richard Nock; Tibério S. Caetano; Paul Rivera (NIPS, 2014)

Rademacher Observations, Private Data, and Boosting. - Richard Nock; Giorgio Patrini; Arik Friedman (ICML, 2015)

Loss factorization, weakly supervised learning and label noise robustness. - Giorgio Patrini; Frank Nielsen; Richard Nock; Marcello Carioni (ICML, 2016)

Fast Learning from Distributed Datasets without Entity Matching. - Giorgio Patrini; Richard Nock; Stephen Hardy 002; Tibério S. Caetano (IJCAI, 2016)

The Crossover Process: Learnability meets Protection from Inference Attacks. - Richard Nock; Giorgio Patrini; Finnian Lattimore; Tibério S. Caetano (CoRR, 2016)

Making Neural Networks Robust to Label Noise: a Loss Correction Approach. - Giorgio Patrini; Alessandro Rozza; Aditya Krishna Menon; Richard Nock; Lizhen Qu (CoRR, 2016)

Tsallis Regularized Optimal Transport and Ecological Inference. - Boris Muzellec; Richard Nock; Giorgio Patrini; Frank Nielsen (AAAI, 2017)

Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach. - Giorgio Patrini; Alessandro Rozza; Aditya Krishna Menon; Richard Nock; Lizhen Qu (CVPR, 2017)

Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption. - Stephen Hardy 002; Wilko Henecka; Hamish Ivey-Law; Richard Nock; Giorgio Patrini; Guillaume Smith; Brian Thorne (CoRR, 2017)

Entity Resolution and Federated Learning get a Federated Resolution. - Richard Nock; Stephen Hardy 002; Wilko Henecka; Hamish Ivey-Law; Giorgio Patrini; Guillaume Smith; Brian Thorne (CoRR, 2018)

Three Tools for Practical Differential Privacy. - Koen Lennart van der Veen; Ruben Seggers; Peter Bloem; Giorgio Patrini (CoRR, 2018)

Sinkhorn AutoEncoders. - Giorgio Patrini; Rianne van den Berg; Patrick Forré; Marcello Carioni; Samarth Bhargav 001; Max Welling; Tim Genewein; Frank Nielsen (UAI, 2019)

SEALion: a Framework for Neural Network Inference on Encrypted Data. - Tim van Elsloo; Giorgio Patrini; Hamish Ivey-Law (CoRR, 2019)

The Impact of Record Linkage on Learning from Feature Partitioned Data. - Richard Nock; Stephen Hardy 002; Wilko Henecka; Hamish Ivey-Law; Jakub Nabaglo; Giorgio Patrini; Guillaume Smith; Brian Thorne (ICML, 2021)