Giorgio Patrini

23 papers A* 6A 3Journal 12Unranked 2

Year	Rank	Type	Title / Venue / Authors
2021	A*	`conf`	The Impact of Record Linkage on Learning from Feature Partitioned Data. ICML Richard Nock, Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne
2019	J	`jnl`	SEALion: a Framework for Neural Network Inference on Encrypted Data. CoRR Tim van Elsloo, Giorgio Patrini, Hamish Ivey-Law
2019	A	`conf`	Sinkhorn AutoEncoders. UAI Giorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen
2018	J	`jnl`	Entity Resolution and Federated Learning get a Federated Resolution. CoRR Richard Nock, Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Giorgio Patrini, Guillaume Smith, Brian Thorne
2018	J	`jnl`	Sinkhorn AutoEncoders. CoRR Giorgio Patrini, Marcello Carioni, Patrick Forré, Samarth Bhargav, Max Welling, Rianne van den Berg, Tim Genewein, Frank Nielsen
2018	J	`jnl`	Three Tools for Practical Differential Privacy. CoRR Koen Lennart van der Veen, Ruben Seggers, Peter Bloem, Giorgio Patrini
2017	A*	`conf`	Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach. CVPR Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon, Richard Nock, Lizhen Qu
2017	J	`jnl`	Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption. CoRR Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Richard Nock, Giorgio Patrini, Guillaume Smith, Brian Thorne
2017	A*	`conf`	Tsallis Regularized Optimal Transport and Ecological Inference. AAAI Boris Muzellec, Richard Nock, Giorgio Patrini, Frank Nielsen
2016	A*	`conf`	Fast Learning from Distributed Datasets without Entity Matching. IJCAI Giorgio Patrini, Richard Nock, Stephen Hardy, Tibério S. Caetano
2016	J	`jnl`	Fast Learning from Distributed Datasets without Entity Matching. CoRR Giorgio Patrini, Richard Nock, Stephen Hardy, Tibério S. Caetano
2016	A*	`conf`	Loss factorization, weakly supervised learning and label noise robustness. ICML Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni
2016	J	`jnl`	Loss factorization, weakly supervised learning and label noise robustness. CoRR Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni
2016	J	`jnl`	Making Neural Networks Robust to Label Noise: a Loss Correction Approach. CoRR Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon, Richard Nock, Lizhen Qu
2016	J	`jnl`	The Crossover Process: Learnability meets Protection from Inference Attacks. CoRR Richard Nock, Giorgio Patrini, Finnian Lattimore, Tibério S. Caetano
2016	J	`jnl`	Tsallis Regularized Optimal Transport and Ecological Inference. CoRR Boris Muzellec, Richard Nock, Giorgio Patrini, Frank Nielsen
2015	A*	`conf`	Rademacher Observations, Private Data, and Boosting. ICML Richard Nock, Giorgio Patrini, Arik Friedman
2015	J	`jnl`	Rademacher Observations, Private Data, and Boosting. CoRR Richard Nock, Giorgio Patrini, Arik Friedman
2014	—	`conf`	(Almost) No Label No Cry. NIPS Giorgio Patrini, Richard Nock, Tibério S. Caetano, Paul Rivera
2012	J	`jnl`	Combining local search techniques and path following for bimatrix games CoRR Nicola Gatti, Giorgio Patrini, Marco Rocco, Tuomas Sandholm
2012	A	`conf`	Combining local search techniques and path following for bimatrix games. UAI Nicola Gatti, Giorgio Patrini, Marco Rocco, Tuomas Sandholm
2010	—	`conf`	Local Search Methods for Finding a Nash Equilibrium in Two-Player Games. IAT Sofia Ceppi, Nicola Gatti, Giorgio Patrini, Marco Rocco
2010	A	`conf`	Local search techniques for computing equilibria in two-player general-sum strategic-form games. AAMAS Sofia Ceppi, Nicola Gatti, Giorgio Patrini, Marco Rocco