Phase transition in limiting distributions of coherence of high-dimensional random matrices
Journal of Multivariate Analysis
Uncertainty principles and ideal atomic decomposition
IEEE Transactions on Information Theory
On Jiang's asymptotic distribution of the largest entry of a sample correlation matrix
Journal of Multivariate Analysis
Hi-index | 0.00 |
This paper studies the asymptotic behaviors of the pairwise angles among n randomly and uniformly distributed unit vectors in Rp as the number of points n → ∞, while the dimension p is either fixed or growing with n. For both settings, we derive the limiting empirical distribution of the random angles and the limiting distributions of the extreme angles. The results reveal interesting differences in the two settings and provide a precise characterization of the folklore that "all high-dimensional random vectors are almost always nearly orthogonal to each other". Applications to statistics and machine learning and connections with some open problems in physics and mathematics are also discussed.