Paper Info
Title
Local Intrinsic Dimension Estimation by Generalized Linear Modeling.
Abstract
We propose a method for intrinsic dimension estimation. By fitting the power of distance from an inspection point and the number of samples included inside a ball with a radius equal to the distance, to a regression model, we estimate the goodness of fit. Then, by using the maximum likelihood method, we estimate the local intrinsic dimension around the inspection point. The proposed method is show...
Year
DOI
Venue
2017
10.1162/NECO_a_00969
Neural Computation
Field
DocType
Volume
Mathematical optimization,Generalized linear model,Intrinsic dimension,Sufficient dimension reduction,Mathematics
Journal
29
Issue
ISSN
Citations 
7
0899-7667
0
PageRank 
References 
Authors
0.34
11
4
Name
Order
Citations
PageRank
Hideitsu Hino19925.73
Jun Fujiki23310.33
Shotaro Akaho365079.46
Noboru Murata4855170.36