Johnson-Lindenstrauss projection of high dimensional data

Authors

Shuhong Gao, Clemson University
Fiona Knoll, Clemson University
Yue Mao, Clemson University

Document Type

Poster

Publication Date

Spring 2015

Abstract

Johnson and Lindenstrauss (1984) proved that any finite set of data in a high dimensional space can be projected into a low dimensional space with the Euclidean metric information of the set being preserved within any desired accuracy. Such dimension reduction plays a critical role in many applications with massive data. There have been extensive effort in the literature on how to find explicit constructions of Johnson-Lindenstrauss projections. In this poster, we show how algebraic codes over finite fields can be used for fast Johnson-Lindenstrauss projections of data in high dimensional Euclidean spaces. This is joint work with Shuhong Gao and Yue Mao.

Recommended Citation

Gao, Shuhong; Knoll, Fiona; and Mao, Yue, "Johnson-Lindenstrauss projection of high dimensional data" (2015). Graduate Research and Discovery Symposium (GRADS). 122.
https://open.clemson.edu/grads_symposium/122