Applying a randomized nearest neighbors algorithm to dimensionality reduction
Author(s)
Jayaraman, Gautam, 1981-
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Other Contributors
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Joshua B. Tenenbaum.
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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).
Date issued
2003Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.