From the 1 of 7 linked papers with an AI index.
7 papers
Rank deficiency of Bernoulli random matrices for growing corank
Zeyan Song, Hanchao Wang
The paper calculates the asymptotic probability that an n×n Bernoulli random matrix has a corank of at least k when k grows slower than √(log n), showing it equals (1‑p)^{kn} up to…
Failure of Convex-Hull Bounds under Log-Convex Tails
Xuanang Hu, Hanchao Wang
Fix , and let be independent symmetric Weibull random variables, that is, \[ \textsf{P}(|X_i|>t)=e^{-t^r},\qquad t\ge 0. \] We prove that there is no co…
The eigenvalue gap of inhomogeneous symmetric discrete random matrix
Zeyan Song, Hanchao Wang
Let A be an n x n symmetric random matrix whose upper-triangular entries are independent and follow possibly non-identical subgaussian distributions. This paper investigates the sp…
The exact group-sparse recovery for block diagonal matrices with subexponential entries
Guozheng Dai, Tiankun Diao, Hanchao Wang
We study block-diagonal random matrices with i.i.d. subexponential entries and show that, despite their highly structured form, they already guarantee exact sparse recovery from a…
Uniform Concentration for -subexponential Random Operators
Tiankun Diao, Xuanang Hu, Vladimir V. Ulyanov +1
Random matrices acting on structured sets play a fundamental role in high-dimensional geometry, compressed sensing, and randomized algorithms. Existing results primarily focus on s…
The Rank and Singular Values of the Inhomogeneous Subgaussian Random Matrices
Guozheng Dai, Zeyan Song, Hanchao Wang
Let A be an n*n random matrix with mean zero and independent inhomogeneous non-constant subgaussian entries. We get that for any k<c\sqrt{n}, the probability of the matrix has a lo…