Thumbnail
Access Restriction
Subscribed

Author Moran, Shay ♦ Yehudayoff, Amir
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2016
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword PAC learning ♦ VC dimension ♦ Sample compression schemes
Abstract Sample compression schemes were defined by Littlestone and Warmuth (1986) as an abstraction of the structure underlying many learning algorithms. Roughly speaking, a sample compression scheme of size $\textit{k}$ means that given an arbitrary list of labeled examples, one can retain only $\textit{k}$ of them in a way that allows us to recover the labels of all other examples in the list. They showed that compression implies probably approximately correct learnability for binary-labeled classes and asked whether the other direction holds. We answer their question and show that every concept class $\textit{C}$ with VC dimension $\textit{d}$ has a sample compression scheme of size exponential in $\textit{d}.$
ISSN 00045411
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2016-06-01
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 63
Issue Number 3
Page Count 10
Starting Page 1
Ending Page 10


Open content in new tab

   Open content in new tab
Source: ACM Digital Library