Distribution-Dependent Weighted Union Bound.
distribution-dependent weights
finite number of hypothesis
statistical learning theory
union bound
weighted union bound
Journal
Entropy (Basel, Switzerland)
ISSN: 1099-4300
Titre abrégé: Entropy (Basel)
Pays: Switzerland
ID NLM: 101243874
Informations de publication
Date de publication:
12 Jan 2021
12 Jan 2021
Historique:
received:
11
11
2020
revised:
09
01
2021
accepted:
10
01
2021
entrez:
15
1
2021
pubmed:
16
1
2021
medline:
16
1
2021
Statut:
epublish
Résumé
In this paper, we deal with the classical Statistical Learning Theory's problem of bounding, with high probability, the true risk R(h) of a hypothesis
Identifiants
pubmed: 33445650
pii: e23010101
doi: 10.3390/e23010101
pmc: PMC7827710
pii:
doi:
Types de publication
Journal Article
Langues
eng
Références
Stat Sci. 2009 Nov;24(4):398-413
pubmed: 20711421
Neural Netw. 2016 Oct;82:62-75
pubmed: 27474843
Entropy (Basel). 2018 Jun 06;20(6):
pubmed: 33265534