4.4 Article

CONSTRUCTIVE DISCREPANCY MINIMIZATION FOR CONVEX SETS

Journal

SIAM JOURNAL ON COMPUTING
Volume 46, Issue 1, Pages 224-234

Publisher

SIAM PUBLICATIONS
DOI: 10.1137/141000282

Keywords

discrepancy theory; discrete math; convex geometry

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A classical theorem of Spencer shows that any set system with n sets and n elements admits a coloring of discrepancy O(root n). Recent exciting work of Bansal, Lovett, and Meka shows that such colorings can be found in polynomial time. In fact, the Lovett-Meka algorithm finds a half integral point in any large enoughpolytope. However, their algorithm crucially relies on the facet structure and does not apply to general convex sets. We show that for any symmetric convex set K with Gaussian measure at least e-n/500, the following algorithm finds a point y epsilon K boolean AND [-1, 1](n) with O(n) coordinates in +/- 1: (1) take a random Gaussian vector x; (2) compute the point y in K boolean AND[-1, 1](n) that is closest to x; (3) return y. This provides another truly constructive proof of Spencer's theorem and the first constructive proof of a theorem of Gluskin and Giannopoulos.

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