Invertibility of random submatrices via tail decoupling and a Matrix Chernoff Inequality

Details Invertibility of random submatrices via tail decoupling and a Matrix Chernoff Inequality Invertibility of random submatrices via tail decoupling and a Matrix Chernoff Inequality

2011-03-15

arxiv.org/abs/1103.3063v3

Mathematics

Probability

Scientific paper

Let $X$ be a $n\times p$ matrix with coherence $\mu(X)=\max_{j\neq j'} |X_j^tX_{j'}|$. We present a simplified and improved study of the quasi-isometry property for most submatrices of $X$ obtained by uniform column sampling. Our results depend on $\mu(X)$, $\|X\|$ and the dimensions with explicit constants, which improve the previously known values by a large factor. The analysis relies on a tail decoupling argument, of independent interest, and a recent version of the Non-Commutative Chernoff inequality (NCCI).

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