Invertibility of random submatrices via tail decoupling and a Matrix   Chernoff Inequality
  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). 
St\'ephane Chr\'etien and S\'ebastien Darses
math.PR math.ST stat.TH