Local Rademacher complexity: sharper risk bounds with and without unlabeled samples
type: Item
instance of: scholarly article
title: Local Rademacher complexity: sharper risk bounds with and without unlabeled samples
zbMATH Open document ID: 1394.68306
author: Luca Oneto
author: Alessandro Ghio
author: Sandro Ridella
author: Davide Anguita
published in: Neural Networks
publication date: 2018-08-30T00:00:00Z
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6929194
zbMATH Keywords: statistical learning theory
zbMATH Keywords: performance estimation
zbMATH Keywords: local Rademacher complexity
zbMATH Keywords: unlabeled samples
Wikidata QID: Q50597884
MaRDI profile type: Publication
full work available at URL: j.neunet.2015.02.006
OpenAlex ID: W2009784682
cites work: Fast learning rates for plug-in classifiers
cites work: Model selection and error estimation
cites work: Q3046694
cites work: Local Rademacher complexities
cites work: 10.1162/153244303321897690
cites work: A sharp concentration inequality with applications
cites work: Q4907706
cites work: A Bennett concentration inequality and its application to suprema of empirical processes
cites work: Advanced Lectures on Machine Learning
cites work: 10.1162/153244302760200704
cites work: Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)
cites work: Oracle inequalities in empirical risk minimization and sparse recovery problems. École d'Été de Probabilités de Saint-Flour XXXVIII-2008.
cites work: Q3997990
cites work: Tighter PAC-Bayes bounds through distribution-dependent priors
cites work: PAC-Bayesian Theory
cites work: Q3496342
cites work: An improved analysis of the Rademacher data-dependent bound using its self bounding property
cites work: Q5405232
cites work: Are Loss Functions All the Same?
cites work: Fast rates for support vector machines using Gaussian kernels
cites work: The Glivenko-Cantelli problem
cites work: Q5069420
cites work: Q4261789
DBLP publication ID: journals/nn/OnetoGRA15
DOI: 10.1016/J.NEUNET.2015.02.006
description: scientific article; zbMATH DE number 6929194