Xiaoyu Dong
Let $R_n$ be a $n \times n$ random matrix with i.i.d. subgaussian entries. Let $M$ be a $n \times n$ deterministic matrix with norm $\lVert M \rVert \le n^γ$ where $1/2<γ<1$. The goal of this paper is to give a general estimate of the smallest singular value of the sum $R_n + M$, which improves an earlier result of Tao and Vu.
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We derive a lower bound on the smallest singular value of a random $d$-regular matrix, that is, the adjacency matrix of a random $d$-regular directed graph. More precisely, let $C_1<d< c_1 n/\log^2 n$ and let $\mathcal{M}_{n,d}$ be the set of all $0/1$-valued square $n\times n$ matrices such that each row and each column of a matrix $M\in \mathcal{M}_{n,d}$ has exactly $d$ ones. Let $M$ be uniformly distributed on $\mathcal{M}_{n,d}$. Then the smallest singular value $s_{n} (M)$ of $M$ is greater than $c_2 n^{-6}$ with probability at least $1-C_2\log^2 d/\sqrt{d}$, where $c_1$, $c_2$, $C_1$, a…
We prove an estimate on the smallest singular value of a multiplicatively and additively deformed random rectangular matrix. Suppose $n\le N \le M \le ΛN$ for some constant $Λ\ge 1$. Let $X$ be an $M\times n$ random matrix with independent and identically distributed entries, which have zero mean, unit variance and arbitrarily high moments. Let $T$ be an $N\times M$ deterministic matrix with comparable singular values $c\le s_{N}(T) \le s_{1}(T) \le c^{-1}$ for some constant $c>0$. Let $A$ be an $N\times n$ deterministic matrix with $\|A\|=O(\sqrt{N})$. Then we prove that for any $ε>0$, the sm…
Smallest Singular Value for Perturbations of Random Permutation Matrices
我们采取了第一个小的步骤，扩展的有效性Rudelson-Vershynin型估计的一些稀疏的随机矩阵，这里的随机置换矩阵。本文给出了一个大的随机矩阵D+M的最小奇异值的上（下）界，这里M是一个均匀采样的随机置换矩阵，D是对角矩阵。当D本身是随机的且对角线上有独立同分布项时，利用负漂移随机游动的经典理论，得到了一个Rudelson-Vershynin型估计.
Let $A = (a_{ij})$ be a square $n\times n$ matrix with i.i.d. zero mean and unit variance entries. Rudelson and Vershynin showed that the upper bound for a smallest singular value $s_n(A)$ is of order $n^{-\frac12}$ with probability close to one under additional assumption on entries of $A$ that $\mathbb{E}a^4_{11} < \infty$. We remove the assumption on the fourth moment and show the upper bound assuming only $\mathbb{E}a^2_{11} = 1.$
We derive estimates for the largest and smallest singular values of sparse rectangular $N\times n$ random matrices, assuming $\lim_{N,n\to\infty}\frac nN=y\in(0,1)$. We consider a model with sparsity parameter $p_N$ such that $Np_N\sim \log^{α}N$ for some $α>1$, and assume that the moments of the matrix elements satisfy the condition $\mathbf E|X_{jk}|^{4+δ}\le C<\infty$. We assume also that the entries of matrices we consider are truncated at the level $(Np_N)^{\frac12-\varkappa}$ with $\varkappa:=\fracδ{2(4+δ)}$.
Let $n,k\geq 1$ and let $G$ be the $n\times n$ random matrix with i.i.d. standard real Gaussian entries. We show that there are constants $c_k,C_k>0$ depending only on $k$ such that the smallest singular value of $G^k$ satisfies $$ c_k\,t\leq {\mathbb P}\big\{s_{\min}(G^k)\leq t^k\,n^{-1/2}\big\}\leq C_k\,t,\quad t\in(0,1], $$ and, furthermore, $$ c_k/t\leq {\mathbb P}\big\{\|G^{-k}\|_{HS}\geq t^k\,n^{1/2}\big\}\leq C_k/t,\quad t\in[1,\infty), $$ where $\|\cdot\|_{HS}$ denotes the Hilbert-Schmidt norm.
Let $δ>1$ and $β>0$ be some real numbers. We prove that there are positive $u,v,N_0$ depending only on $β$ and $δ$ with the following property: for any $N,n$ such that $N\ge \max(N_0,δn)$, any $N\times n$ random matrix $A=(a_{ij})$ with i.i.d. entries satisfying $\sup\limits_{λ\in {\mathbb R}}{\mathbb P}\bigl\{|a_{11}-λ|\le 1\bigr\}\le 1-β$ and any non-random $N\times n$ matrix $B$, the smallest singular value $s_n$ of $A+B$ satisfies ${\mathbb P}\bigl\{s_n(A+B)\le u\sqrt{N}\bigr\}\le \exp(-vN)$. The result holds without any moment assumptions on distribution of the entries of $A$.
On generic chaining and the smallest singular value of random matrices with heavy tails
我们提出了一个非常一般的链接方法，它允许一个控制的经验过程$\sup_{h \in H} |N^{-1}\sum_{i=1}^N h^2(X_i)-\E h^2|$的上确界在相当一般的情况下。我们使用这种方法建立两个主要结果。首先，一个定量（非渐近）版本的经典白音定理的奇异值的随机矩阵的i.i.d的项目，有沉重的尾巴，第二，尖锐的估计二次经验过程时，$H=\{\inr{t,\cdot} : t \in T\}$，$T \subset \R^n$和$μ$是一个各向同性的，无条件的，对数凹措施。
We obtain lower tail estimates for the smallest singular value of random matrices with independent but non-identically distributed entries. Specifically, we consider $n\times n$ matrices with complex entries of the form \[ M = A\circ X + B = (a_{ij}ξ_{ij} + b_{ij}) \] where $X=(ξ_{ij})$ has iid centered entries of unit variance and $A$ and $B$ are fixed matrices. In our main result we obtain polynomial bounds on the smallest singular value of $M$ for the case that $A$ has bounded (possibly zero) entries, and $B= Z\sqrt{n}$ where $Z$ is a diagonal matrix with entries bounded away from zero. As …
Let $\{a_{ij}\}$ $(1\le i,j<\infty)$ be i.i.d. real valued random variables with zero mean and unit variance and let an integer sequence $(N_m)_{m=1}^\infty$ satisfy $m/N_m\longrightarrow z$ for some $z\in(0,1)$. For each $m\in{\mathbb N}$ denote by $A_m$ the $N_m\times m$ random matrix $(a_{ij})$ $(1\le i\le N_m,1\le j\le m)$ and let $s_{m}(A_m)$ be its smallest singular value. We prove that the sequence $\bigl({N_m}^{-1/2} s_{m}(A_m)\bigr)_{m=1}^\infty$ converges to $1-\sqrt{z}$ almost surely. Our result does not require boundedness of any moments of $a_{ij}$'s higher than the $2$-nd and res…
The smallest singular value of a random rectangular matrix
我们证明了随机亚高斯矩阵最小奇异值的最佳估计，该估计对所有固定维度都有效。对于具有独立同分布次高斯元素的N × n矩阵A，A的最小奇异值以高概率至少为\sqrt{N} - \sqrt{n-1}阶.并给出了概率的精确估计。
Least singular values of shifted sparse random combinatorial matrices
研究稀疏随机组合矩阵的谱分布，证明在特定条件下，经缩放后的矩阵经验谱分布收敛到圆形定律，同时获得移位矩阵最小奇异值的下界。
Bounding the smallest singular value of a random matrix without concentration
给定$X$为${\mathbb{R}}^n$中的随机向量，将$X_1,...,X_N$设置为$X$的独立副本，并将$Γ=\frac{1}{\sqrt{N}}\sum_{i=1}^N <X_i,\cdot>e_i$设为行为$\frac{X_1}{\sqrt{N}},\dots, \frac{X_N}{\sqrt{N}}$的矩阵。我们得到了尖锐的概率下界的最小奇异值$λ_{\min}(Γ)$在一个相当一般的情况下，特别是，假设$X$是一个各向同性的随机向量，其中$\sup_{t\in S^{n-1}}{\mathbb{E}}|<t,X>|^{2+η} \leq L$的一些$L,η>0$。我们的结果意味着一个白阴型的下限保持$η>2$，并在一个对数因子，$η=2$以及。在不对欧几里德范数$\|X\|_{\ell_2^n}$作任何额外假设的情况下，该界限成立。此外，我们建立了一个非平凡的下界，即使没有任何更高的时刻的假设（对应的情况$η=0$），如果线性形式满足一个弱的“小球”属性。
Suppose $X$ is an $N \times n$ complex matrix whose entries are centered, independent, and identically distributed random variables with variance $1/n$ and whose fourth moment is of order ${\mathcal O}(n^{-2})$. In the first part of the paper, we consider the non-Hermitian matrix $X A X^* - z$, where $A$ is a deterministic matrix whose smallest and largest singular values are bounded below and above respectively, and $z\neq 0$ is a complex number. Asymptotic probability bounds for the smallest singular value of this model are obtained in the large dimensional regime where $N$ and $n$ diverge t…
We consider the least singular value of a large random matrix with real or complex i.i.d. Gaussian entries shifted by a constant $z\in\mathbb{C}$. We prove an optimal lower tail estimate on this singular value in the critical regime where $z$ is around the spectral edge thus improving the classical bound of [Sankar, Spielman, Teng, 2006] in the edge regime. Lacking Brézin-Hikami formulas in the real case, we rely on the superbosonization formula [Littelmann, Sommers, Zirnbauer, 2008].
The smallest singular value of sparse discrete random matrices
本文构建简单框架证明独立同分布稀疏离散随机矩阵的近似 Spielman-Teng 最小奇异值定理，并推广至 $μ$-lazy 随机变量情形。
An upper bound on the smallest singular value of dense random combinatorial matrices
本文研究密集随机组合矩阵的最小奇异值，证明其上界为$\sqrt{d}/(\varepsilon^2 n)$，确认其通常规模为$\mathcal{O}(n^{-1/2})$。
Smallest singular value of sparse random matrices
本文将独立元随机矩阵最小奇异值的概率估计推广到一类稀疏随机矩阵。我们表明，人们可以放松以前使用的条件的一致有界的方差从下面。这允许我们考虑具有空元素的矩阵，或者更一般地，具有小方差的元素。我们的结果不假设一个随机矩阵的条目的分布相同，并有助于澄清的作用的方差的条目。我们还表明，它是足够的，要求从上面的$r$ -th时刻，$r > 2$，相应的条目的有界性。
We derive a precise asymptotic formula for the density of the small singular values of the real Ginibre matrix ensemble shifted by a complex parameter $z$ as the dimension tends to infinity. For $z$ away from the real axis the formula coincides with that for the complex Ginibre ensemble we derived earlier in [arXiv:1908.01653]. On the level of the one-point function of the low lying singular values we thus confirm the transition from real to complex Ginibre ensembles as the shift parameter $z$ becomes genuinely complex; the analogous phenomenon has been well known for eigenvalues. We use the s…
Let $A$ be the adjacency matrix of a uniformly random $d$-regular digraph on $n$ vertices, and suppose that $\min(d,n-d)\geqλn$. We show that for any $κ\geq 0$, \[\mathbb{P}[s_n(A)\leqκ]\leq C_λκ\sqrt{n}+2e^{-c_λn}.\] Up to the constants $C_λ, c_λ> 0$, our bound matches optimal bounds for $n\times n$ random matrices, each of whose entries is an i.i.d $\text{Ber}(d/n)$ random variable. The special case $κ= 0$ of our result confirms a conjecture of Cook regarding the probability of singularity of dense random regular digraphs.
The smallest singular value of large random rectangular Toeplitz and circulant matrices
本文研究大型随机矩形Toeplitz与循环矩阵的最小奇异值，证明其最小特征值收敛于零，并给出收敛速率的下界（快于多对数但慢于多项式）及矩形循环矩阵的多项式上界。
On the smallest singular value of the product of random and deterministic matrices
研究随机矩阵\(A\)与确定性矩阵\(M\)乘积的最小奇异值，通过对随机矩阵元素条件设定，证明存在依赖\(K\)和\(\kappa\)的常数使相关概率不等式成立，高斯情形下该估计精确。
The smallest singular value and condition number play important roles in numerical linear algebra and the analysis of algorithms. In numerical analysis with randomness, many previous works make Gaussian assumptions, which are not general enough to reflect the arbitrariness of the input. To overcome this drawback, we prove the first quantitative universality for the smallest singular value and condition number of random matrices. Moreover, motivated by the study of smoothed analysis that random perturbation makes deterministic matrices well-conditioned, we consider an analog for random matrices…
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 $0$ and variance $1$, \[\mathbb{P}[s_n(A_n) \le ε/\sqrt{n}] \le O_ξ(ε^{1/8} + \exp(-Ω_ξ(n^{1/2}))) \quad \text{for all } ε\ge 0.\] This improves a result of Vershynin, who obtained such a bound with $n^{1/2}$ replaced by $n^{c}$ for a small constant $c$, and $1/8$ replaced by $(1/8) + η$ (with implicit constants also depending on $η> 0$). Furthermore, when $ξ$ is a Rademacher random variable, we prove that \[\mathbb{P}[s_n…
The smallest singular value of signed random combinatorial matrices
研究了有符号随机组合矩阵的最小奇异值，证明了其在特定条件下概率分布，并展示了该方法在受限环境下的应用。
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 contributions to the study of $s_n(A+M)$, the smallest singular value of $A+M$. (1) We show that for all $ε\geq 0$, $$\mathbb{P}[s_n(A + M) \leq ε] = O(ε\sqrt{n}) + 2e^{-Ω(n)},$$ provided only that $A$ has $Ω(n)$ singular values which are $O(\sqrt{n})$. This extends a well-known result of Rudelson and Vershynin, which requires all singular values of $A$ to be $O(\sqrt{n})$. (2) We show that any bound of the form $$\…
On the Smallest Singular Value of Log-Concave Random Matrices
本文针对各向同性对数凹随机矩阵，在无条件分布（无独立性假设）、列独立且$N\geq n$、足够高（$N\geq (1+λ)n$）三种情况下，证明了其最小奇异值的严格下界尾估计。
We are concerned with the small ball behavior of the smallest singular value of random matrices. Often, establishing such results involves, in some capacity, a discretization of the unit sphere. This requires bounds on the norm of the matrix, and the latter bounds require strong assumptions on the distribution of the entries, such as bounded fourth moments (for a weak estimate), sub-gaussian tails (for a strong estimate), and structural assumptions such as mean zero and variance one. Recently, Rebrova and Tikhomirov developed a discretization procedure which does not rely on strong tail assump…
Let $Q_n$ be a random $n\times n$ matrix with entries in $\{0,1\}$ whose rows are independent vectors of exactly $n/2$ zero components. We show that the smallest singular value $s_n(Q_n)$ of $Q_n$ satisfies \[ \mathbb{P}\Big\{s_n(Q_n)\le \frac{\varepsilon}{\sqrt{n}}\Big\} \le C\varepsilon + 2 e^{-cn} \quad \forall \varepsilon \ge 0, \] which is optimal up to the constants $C,c>0$. This improves on earlier results of Ferber, Jain, Luh and Samotij, as well as Jain. In particular, for $\varepsilon=0$, we obtain the first exponential bound in dimension for the singularity probability \[ \mathbb{P}…
Random matrices: The distribution of the smallest singular values
设$\a$是均值为零、方差为1的实值随机变量。令$M_n(\a)$表示其条目是$\a$的iid副本的$n \times n$随机矩阵，并且$σ_n(M_n(\a))$表示$M_n(\a)$的最小奇异值。（$σ_n(M_n(\a))^2$通常也被解释为Wishart矩阵$M_n M_n^{\ast}$的最小特征值。）我们表明，（在有限矩假设下）的概率分布$n σ_n(M_n(\a))^2$是{ \it通用}的意义上说，它不依赖于分布的$\a$。特别地，当$a$是实高斯时，它收敛到与特殊情况相同的极限分布。(The在这种情况下，Edelman明确计算了极限分布。）对于均值为零的复值随机变量，实部和虚部方差为1/2，协方差为零，我们也证明了类似的结果。对于任何固定的$k$（甚至对于$k$作为$n$的小幂增长）和矩形矩阵，对于$M_n(\a)$的底部$k$奇异值的联合分布也得到了类似的结果。我们的方法的动机是从组合学和理论计算机科学的一般思想的“属性测试”。这似乎是随机矩阵谱研究的一种新方法，并结合了数学各个领域的工具。
The smallest singular value for rectangular random matrices with Lévy entries
本文研究元素服从重尾 Lévy 分布的矩形随机矩阵最小奇异值，证明其在高概率下可确定至对数因子，并给出新的下界及扰动矩阵情形。
We show that for an $n\times n$ random matrix $A$ with independent uniformly anti-concentrated entries, such that $\mathbb{E} ||A||^2_{HS}\leq K n^2$, the smallest singular value $σ_n(A)$ of $A$ satisfies $$ P\left( σ_n(A)\leq \frac{\varepsilon}{\sqrt{n}} \right) \leq C\varepsilon+2e^{-cn},\quad \varepsilon \ge 0. $$ This extends earlier results of Rudelson and Vershynin, and Rebrova and Tikhomirov by removing the assumption of mean zero and identical distribution of the entries across the matrix, as well as the recent result of Livshyts, where the matrix was required to have i.i.d. rows. Our …
Let $M_n$ be an $n\times n$ random matrix with i.i.d. Bernoulli(p) entries. We show that there is a universal constant $C\geq 1$ such that, whenever $p$ and $n$ satisfy $C\log n/n\leq p\leq C^{-1}$, \begin{align*} {\mathbb P}\big\{\mbox{$M_n$ is singular}\big\}&=(1+o_n(1)){\mathbb P}\big\{\mbox{$M_n$ contains a zero row or column}\big\}\\ &=(2+o_n(1))n\,(1-p)^n, \end{align*} where $o_n(1)$ denotes a quantity which converges to zero as $n\to\infty$. We provide the corresponding upper and lower bounds on the smallest singular value of $M_n$ as well.
The smallest singular value of inhomogenous random rectangular matrices
本文研究独立但非齐次元素的随机矩形矩阵最小奇异值，在有界 $2+\beta$ 矩或均匀反集中条件下建立下尾界，并推广已有独立同分布结果。
The least singular value of a random square matrix is O(n^{-1/2})
设A是一个矩阵，其元素是实同分布的。具有单位方差和适当矩假设的中心随机变量。则A的最小奇异值以高概率为n^{-1/2}阶。作者最近证明了这类估计的下估计，本文建立了匹配上估计。
The Singular Values of Lévy's Area Matrix
研究d维布朗运动Lévy面积矩阵的奇异值，推导其密度显式公式，刻画为行列式点过程，并给出大d渐近行为。
The problem of estimating the smallest singular value of random square matrices is important in connection with matrix computations and analysis of the spectral distribution. In this survey, we consider recent developments in the study of quantitative invertibility in the non-Hermitian setting, and review some applications of this line of research.
Non-asymptotic theory of random matrices: extreme singular values
经典的随机矩阵理论主要研究随机矩阵维数增长到无穷大时的渐近谱性质。与此同时，从凸几何到泛函分析再到信息论，许多最近的应用都是用固定维的随机矩阵来操作的。本文研究了独立元随机矩阵极值奇异值的非渐近理论。本文主要讨论了随机矩阵硬边（最小奇异值）的几何估计方法。
Phase transition for the bottom singular vector of rectangular random matrices
本文研究重尾矩形随机矩阵最小奇异值对应右奇异向量的局域化长度，证明其随参数跨过临界值时发生相变，并揭示该相变机制与顶部奇异向量情形本质不同。
Computing extreme singular values of free operators
本研究依托随机矩阵理论的内在自由性原理，针对非自伴情形下自由算子的极端奇异值计算问题，给出了对应的变分公式，拓展了原有自伴情形下的谱边计算方法。
The Littlewood-Offord Problem and invertibility of random matrices
本文证明了具有独立元素的随机n × n矩阵的最小奇异值分布的两个基本定理。在最小矩的假设下，我们证明了最小的奇异值是n^{-1/2}阶的，这是高斯矩阵的最佳。此外，我们给出了尾概率的最优估计。这是Littlewood-Offord问题中一个新的和本质上尖锐的估计的结果：对于i.i.d.随机变量X_k和实数a_k，决定了a_k X_k之和位于某个数v附近的概率P.对于相同数量级的任意系数a_k，我们证明了它们本质上位于长度为1/p的等差数列中.
A distance theorem for inhomogenous random rectangular matrices
本文证明非齐次随机矩形矩阵列空间与独立随机向量的距离小球估计，并提出 Randomized Logarithmic LCD 工具以推广已有距离定理。
Very recently, we have shown how the harmonic analysis approach can be modified to deal with products of general Hermitian and complex random matrices at finite matrix dimension. In the present work, we consider the particular product of a multiplicative Pólya ensemble on the complex square matrices and a Gaussian unitary ensemble (GUE) shifted by a constant multiplicative of the identity. The shift shall show that the limiting hard edge statistics of the product matrix is weakly dependent on the local spectral statistics of the GUE, but depends more on the global statistics via its Stieltjes …
Extreme singular values of inhomogeneous sparse random rectangular matrices
本研究基于非回溯算子与Ihara-Bass公式，提出统一方法界定非齐次稀疏随机矩形矩阵的极端奇异值，给出概率界并将Bai-Yin定理推广至稀疏情形。
We prove the dynamic programming principle (DPP) in a class of problems where an agent controls a $d$-dimensional diffusive dynamics via both classical and singular controls and, moreover, is able to terminate the optimisation at a time of her choosing, prior to a given maturity. The time-horizon of the problem is random and it is the smallest between a fixed terminal time and the first exit time of the state dynamics from a Borel set. We consider both the cases in which the total available fuel for the singular control is either bounded or unbounded. We build upon existing proofs of DPP and e…
A class of sparse Johnson--Lindenstrauss transforms and analysis of their extreme singular values
本文提出一类稀疏 JL 变换（每列期望非零元素数为 s 的 s-哈希类矩阵），证明其为 JLTs，并利用次高斯性质和几何泛函分析估计极端奇异值，进而得到其极限行为及 GOE Tracy--Widom 分布，对无导数优化中子空间维度选择有重要意义。
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