How Nonconformity Functions and Difficulty of Datasets Impact the Efficiency of Conformal Classifiers

Reference : How Nonconformity Functions and Difficulty of Datasets Impact the Efficiency of Confo...


	Document type :	Scientific congresses, symposiums and conference proceedings : Poster
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/49341

Title :	How Nonconformity Functions and Difficulty of Datasets Impact the Efficiency of Conformal Classifiers
Language :	English
Author, co-author :	Aleksandrova, Marharyta [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
	Chertov, Oleg [National Technical University of Ukraine ”Igor Sikorsky Kyiv Polytechnic Institute”]
Publication date :	Jul-2021
Peer reviewed :	Yes
Event name :	Workshop on Distribution-Free Uncertainty Quantification at ICML 2021
Event date :	24-07-2021
Target :	Researchers ; Professionals
Permalink :	http://hdl.handle.net/10993/49341
Other URL :	https://arxiv.org/abs/2108.05677

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	File	Commentary	Version	Size	Access
Open access	ICML-DFUQ-2021_paper.pdf		Author preprint	1.04 MB	View/Open

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