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COLT
2007
Springer

Sketching Information Divergences

13 years 9 months ago
Sketching Information Divergences
When comparing discrete probability distributions, natural measures of similarity are not p distances but rather are informationdivergences such as Kullback-Leibler and Hellinger. This paper considers some of the issues related to constructing small-space sketches of distributions, a concept related to dimensionality-reduction, such that these measures can be approximately computed from the sketches. Related problems for p distances are reasonably well understood via a series of results including Johnson, Lindenstrauss [27, 18], Alon, Matias, Szegedy [1], Indyk [24], and Brinkman, Charikar [8]. In contrast, almost no analogous results are known to date about constructing sketches for the information-divergences used in statistics and learning theory.
Sudipto Guha, Piotr Indyk, Andrew McGregor
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where COLT
Authors Sudipto Guha, Piotr Indyk, Andrew McGregor
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