Applying a randomized nearest neighbors algorithm to dimensionality reduction
Name
53827547-MIT.pdf
Description
Full printable version
Size
4.05 MB
Format
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Checksum (MD5)
bc8b7702b23734a377b0b3a72608be01
Author(s)
Jayaraman, Gautam, 1981-
Advisor(s)
Joshua B. Tenenbaum.
Date Issued
2003
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, I implemented a randomized nearest neighbors algorithm in order to optimize an existing dimensionality reduction algorithm. In implementation I resolved details that were not considered in the design stage, and optimized the nearest neighbor system for use by the dimensionality reduction system. By using the new nearest neighbor system as a subroutine, the dimensionality reduction system runs in time O(n log n) with respect to the number of data points. This enables us to examine data sets that were prohibitively large before.
Description
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
Includes bibliographical references (p. 95-96).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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