We introduce the following hidden hubs model H(n, k, σ0, σ1): the input is an n × n random matrix A with a subset S of k special rows (hubs); entries in rows outside S are generated from the Gaussian distribution p0 = N(0, σ 0), while for each row in S, an unknown subset of k of its entries are generated from p1 = N(0, σ 1), σ1 > σ0, and the rest of the entries from p0. The special rows with hi...