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Author Chazelle, Bernard ♦ Seshadhri, C.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Computational geometry ♦ Sublinear algorithms
Abstract We investigate a new class of geometric problems based on the idea of online error correction. Suppose one is given access to a large geometric dataset though a query mechanism; for example, the dataset could be a terrain and a query might ask for the coordinates of a particular vertex or for the edges incident to it. Suppose, in addition, that the dataset satisfies some known structural property $\textit{P}$ (for example, monotonicity or convexity) but that, because of errors and noise, the queries occasionally provide answers that violate $\textit{P}.$ Can one design a filter that modifies the query's answers so that (i) the output satisfies $\textit{P};$ (ii) the amount of data modification is minimized? We provide upper and lower bounds on the complexity of online reconstruction for convexity in 2D and 3D.
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 2011-07-01
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 58
Issue Number 4
Page Count 32
Starting Page 1
Ending Page 32


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Source: ACM Digital Library