Abstract
An approximate Spielman-Teng theorem for the least singular value sn(Mn) of a random n × n square matrix Mn is a statement of the following form: there exist constants C, c > 0 such that for all η > 0, Pr(sn(Mn) ≤ η) ≲ nCη + exp(−nc). The goal of this paper is to develop a simple and novel framework for proving such results for discrete random matrices. As an application, we prove an approximate Spielman-Teng theorem for {0, 1}-valued matrices, each of whose rows is an independent vector with exactly n/2 zero components. This improves on previous work of Nguyen and Vu, and is the first such result in a ‘truly combinatorial’ setting.
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