Ashwin Sah

activity

20182022

most citedDiagonal Ramsey via effective quasirandomness

6 citations · 9 across the 13 of their papers we have counts for

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Showing math.PRShow all

7 papers · 1 filter

math.PR2022

Optimal minimization of the covariance loss

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

Let $X$ be a random vector valued in $R^{m}$ such that $∥ X ∥_{2} \leq 1$ almost surely. For every $k \geq 3$ , we show that there exists a sigma algebra $F$ generat…

math.PR2021

Random symmetric matrices: rank distribution and irreducibility of the characteristic polynomial

Asaf Ferber, Vishesh Jain, Ashwin Sah +1

Conditional on the extended Riemann hypothesis, we show that with high probability, the characteristic polynomial of a random symmetric ${\pm 1}$ -matrix is irreducible. This addr…

math.PR2021

Rank deficiency of random matrices

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

Let $M_{n}$ be a random $n \times n$ matrix with i.i.d. $Bernoulli (1/2)$ entries. We show that for fixed $k \geq 1$ , \[\lim_{n\to \infty}\frac{1}{n}\log_2\mathbb{P}[\text{corank…

math.PR2020

Optimal and algorithmic norm regularization of random matrices

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

Let $A$ be an $n \times n$ random matrix whose entries are i.i.d. with mean $0$ and variance $1$ . We present a deterministic polynomial time algorithm which, with probability at lea…

math.PR2020

On the smallest singular value of symmetric random matrices

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

We show that for an $n \times n$ random symmetric matrix $A_{n}$ , whose entries on and above the diagonal are independent copies of a sub-Gaussian random variable $ξ$ with mean $0$ an…

math.PR2020

On the smoothed analysis of the smallest singular value with discrete noise

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

Let $A$ be an $n \times n$ real matrix, and let $M$ be an $n \times n$ random matrix whose entries are i.i.d sub-Gaussian random variables with mean $0$ and variance $1$ . We make two…