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Entropy (Basel, Switzerland)|August 27, 2021
Toward Learning Trustworthily from Data Combining Privacy, Fairness, and Explainability: An Application to Face RecognitionDanilo Franco, Luca Oneto, Nicolò Navarin, et al.Neural Networks : the Official Journal of the International Neural Network Society|July 31, 2016
A local Vapnik-Chervonenkis complexityLuca Oneto, Davide Anguita, Sandro RidellaNeural Networks : the Official Journal of the International Neural Network Society|April 17, 2013
An improved analysis of the Rademacher data-dependent bound using its self bounding propertyLuca Oneto, Alessandro Ghio, Davide Anguita, et al.IEEE Transactions on Neural Networks and Learning Systems|November 25, 2014
A deep connection between the Vapnik-Chervonenkis entropy and the Rademacher complexityDavide Anguita, Alessandro Ghio, Luca Oneto, et al.IEEE Transactions on Neural Networks and Learning Systems|May 9, 2014
In-sample and out-of-sample model selection and error estimation for support vector machinesDavide Anguita, Alessandro Ghio, Luca Oneto, et al.Neural Networks : the Official Journal of the International Neural Network Society|March 4, 2015
Local Rademacher Complexity: sharper risk bounds with and without unlabeled samplesLuca Oneto, Alessandro Ghio, Sandro Ridella, et al.IEEE Transactions on Cybernetics|October 28, 2014
Fully Empirical and Data-Dependent Stability-Based BoundsLuca Oneto, Alessandro Ghio, Sandro Ridella, et al.IEEE Transactions on Neural Networks and Learning Systems|July 11, 2018
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph KernelsLuca Oneto, Nicolo Navarin, Michele Donini, et al.IEEE Transactions on Pattern Analysis and Machine Intelligence|May 23, 2025
Robustness-Congruent Adversarial Training for Secure Machine Learning Model UpdatesDaniele Angioni, Luca Demetrio, Maura Pintor, et al.Bioinformatics (Oxford, England)|May 6, 2017
An efficient graph kernel method for non-coding RNA functional predictionNicolò Navarin, Fabrizio CostaPageof 9