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Kexin Yu

Publications and source records attributed to Kexin Yu.

11 recordsLinked to original sources

Exponential singularity and rank bounds for random symmetric matrices

Let $A$ be an $n\times n$ real symmetric random matrix whose entries above the diagonal are independent, each with largest atom at most $β\in (0,1)$. The diagonal entries have an arbitrary joint distribution and are independent of the entries above the diagonal. We prove that \[ \mathbb{P}[\mathrm{rank}(A)\le n-k]\le 2e^{-c_βnk},\qquad 1\le k\le n, \] where $c_β>0$ depends only on $β$. This extends Han's corank bound to the full range $1\le k\le n$. No moment assumptions are needed, and the entries need not be centered or identically distributed. In particular, the case $k=1$ gives an exponential singularity bound under the uniform atom assumption. Our argument also gives a new proof of the exponential singularity bound for symmetric Rademacher matrices obtained by Campos, Jenssen, Michelen, and Sahasrabudhe. For every fixed $p\in (0,1)$, it yields the exponential singularity bound conjectured by Costello and Vu for the adjacency matrix of the Erdős--Rényi random graph $G(n,p)$, where the case $p=1/2$ was previously proved by Han.

math.PR↗

The smallest singular value of products of random combinatorial and deterministic matrices

Let $p\in(0,1/2]$ be fixed, and let $d,n$ be positive integers satisfying $d=pn$. Let $Q_n$ be an $n\times n$ random combinatorial matrix whose rows are independent and uniformly distributed over the vectors in $\{0,1\}^n$ having exactly $d$ ones. For an arbitrary deterministic invertible $n\times n$ matrix $M$, we establish two-sided bounds for the smallest singular value of $Q_nM$. More precisely, for every $\varepsilon\in(0,1)$, \[ \mathbb P\!\left( \varepsilon\le s_n(Q_nM)\cdot \|M^{-1}\|_{\mathrm{HS}} \le \varepsilon^{-2} \right) \ge 1-C\left( \varepsilon+d^{-1/2}+e^{-c\,\operatorname{sr}(M^{-1})} \right)-2e^{-cn}, \] where positive constants $C, c$ depend only on $p$ and $\operatorname{sr}$ denotes the stable rank. Consequently, for any sequence of deterministic invertible matrices $M$ satisfying $\operatorname{sr}(M^{-1})\to\infty$, $s_n(Q_nM)$ is typically of order $\|M^{-1}\|_{\mathrm{HS}}^{-1}$. In particular, taking $M=\mathbf I_n$ recovers the known $n^{-1/2}$ scale for $s_n(Q_n)$.

math.PR↗

An upper bound on the smallest singular value of dense signed random combinatorial matrices

Let $M_n$ be an $n\times n$ random matrix with entries in $\{-1, 0, 1\}$, where each row is independently and uniformly sampled from the set of all vectors in $\{-1, 0, 1\}^n$ containing exactly $d$ nonzero entries, with $d=pn$ for some fixed constant $p\in(0,1/2]$. A recent result by one of the authors gives a lower bound of order $n^{-1/2}$ for the smallest singular value $s_n(M_n)$ of this model with high probability. In this paper, we establish a matching upper bound for $s_n(M_n)$. Specifically, there exists a constant $C_p>0$ depending only on $p$ such that \[ \forall \varepsilon >0 \qquad \mathbb{P} \left( s_n(M_n) \le \frac{\sqrt{d}}{\varepsilon^2 n} \right) \ge 1-C_p\left(\varepsilon + \frac{1}{\sqrt{d}}\right). \] Consequently, in the dense regime, the smallest singular value $s_n(M_n)$ of signed random combinatorial matrices is typically of order $n^{-1/2}$.

math.PR↗

The singularity probability of dense random regular graphs

Let $G_{n,d}$ be a uniformly random simple $d$-regular graph on $n$ vertices, and let $A_n$ be its adjacency matrix. For every fixed $λ\in(0,1/2)$, we prove that for any $λ(n-1)\le d\le(1-λ)(n-1)$, $\mathbb P(A_n\text{ is singular})\le e^{-cn}$, where $c>0$ depends only on $λ$, and $n$ is sufficiently large with $nd$ even.

math.PR↗

Rank and Invertibility of Dense Signed Random Regular Matrices

Let $A$ be the (non-symmetric) adjacency matrix of a uniformly random $d$-regular directed graph on $n$ vertices, and let $Ξ$ be independent of $A$ with i.i.d. Rademacher entries. Suppose that $\min(d,n-d)\geλn$ for some fixed $λ\in(0,1/2]$. We show that there exists $c > 0$, depending only on $λ$, such that \[ \mathbf P_{A,Ξ}\{\operatorname{rank}(A\circΞ)\le n-k\}\le e^{-c nk},\qquad 1\le k\le n. \] As an ingredient in the proof of the rank bound, we use the case $κ=0$ of the following quantitative smallest singular value estimate: \[ \mathbf P_{A,Ξ}\{s_n(A\circΞ)\leκ\} \le Cκ\sqrt n+e^{-c' n}, \qquad κ\ge0, \] where $C,c'>0$ depend only on $λ$.

math.PR↗

Large corank of dense random regular digraphs

Let $1\le k\le n$ and let $A$ be the adjacency matrix of a uniformly random $d$-regular directed graph on $n$ vertices. Suppose that $λn\le d \le (1-λ)n$ for a fixed $0<λ\le 1/2$. We show that there exists $c_λ>0$ depending only on $λ$ such that $$ \mathbb{P}[\operatorname{rank}(A)\le n-k]\le 2e^{-c_λ kn}. $$ This gives a large corank extension of the exponential singularity bound of Jain, Sah, and Sawhney.

math.PR↗

The smallest singular value of signed random combinatorial matrices

Let $M_n$ be an $n\times n$ signed random combinatorial matrix whose rows are independent and uniformly distributed over the set of $\{-1,0,1\}$-vectors with exactly $n/2$ zero coordinates. Despite the dependence induced by the row constraints, we prove that there exist constants $C,c > 0$ such that for any $\varepsilon\ge0$, \begin{align*} \textbf{P}\left(s_{n}(M_n)\le {\varepsilon}{n^{-1/2}}\right)\le C\varepsilon+e^{-cn}. \end{align*} In particular, the probability that $M_n$ is singular is exponentially small. Our approach builds on the Combinatorial Least Common Denominator (CLCD) introduced by Tran and develops the method in the present constrained setting.

math.PR↗

Illuminating the Mass Gap Through Deep Optical Constraint on a Neutron Star Merger Candidate S250206dm

The gravitational wave (GW) event S250206dm, as the first well-localized neutron star merger candidate potentially located in the mass gap, presented a unique opportunity to probe the electromagnetic signatures from such a system. Here we report a deep, multiband search with the new 2.5-meter Wide Field Survey Telescope (WFST), covering about 64% of the localization region up to a 5-sigma limiting magnitude of 23 mag. In total, 12 potential candidates have been identified while none of them are likely related to S250206dm. This non-detection provides the most stringent constraint to date on any associated kilonova. Crucially, an AT 2017gfo-like event at 269 Mpc can be excluded by WFST observations alone. Based on ejecta mass limits, a neutron star-black hole with a large mass ratio (Q >= 3.2) is disfavored. This optical-derived constraint on the mass ratio reaches, for the first time, a precision comparable to that inferred from the GW signal. This work presents the best observation of this type of events until now, and demonstrates the power of rapid, deep follow-up observations to constrain the properties of compact binary progenitors, offering key insights into the constituents of the mass gap.

astro-ph.HE↗

Janus: Leveraging Incremental Computation for Efficient DNS Verification

Existing DNS configuration verification tools face significant issues (e.g., inefficient and lacking support for incremental verification). Inspired by the advancements in recent work of distributed data plane verification and the resemblance be- tween the data plane and DNS configuration, we tackle the challenge of DNS misconfiguration by introducing Janus, a DNS verification tool. Our key insight is that the process of a nameserver handling queries can be transformed into a matching process on a match-action table. With this insight, Janus consists of (1) an efficient data structure for partition query space based on the behaviors, (2) a symbolic execution algorithm that specifies how a single nameserver can efficiently cover all possible queries and ensure the accuracy of verification, (3) a mechanism to support incremental verification with less computational effort. Extensive experiments on real-world datasets (with over 6 million resource records) show that Janus achieves significant speedups, with peak improvements of up to 255.7x and a maximum 6046x reduction in the number of LECs.

cs.NI↗

VL-MedGuide: A Visual-Linguistic Large Model for Intelligent and Explainable Skin Disease Auxiliary Diagnosis

Accurate diagnosis of skin diseases remains a significant challenge due to the complex and diverse visual features present in dermatoscopic images, often compounded by a lack of interpretability in existing purely visual diagnostic models. To address these limitations, this study introduces VL-MedGuide (Visual-Linguistic Medical Guide), a novel framework leveraging the powerful multi-modal understanding and reasoning capabilities of Visual-Language Large Models (LVLMs) for intelligent and inherently interpretable auxiliary diagnosis of skin conditions. VL-MedGuide operates in two interconnected stages: a Multi-modal Concept Perception Module, which identifies and linguistically describes dermatologically relevant visual features through sophisticated prompt engineering, and an Explainable Disease Reasoning Module, which integrates these concepts with raw visual information via Chain-of-Thought prompting to provide precise disease diagnoses alongside transparent rationales. Comprehensive experiments on the Derm7pt dataset demonstrate that VL-MedGuide achieves state-of-the-art performance in both disease diagnosis (83.55% BACC, 80.12% F1) and concept detection (76.10% BACC, 67.45% F1), surpassing existing baselines. Furthermore, human evaluations confirm the high clarity, completeness, and trustworthiness of its generated explanations, bridging the gap between AI performance and clinical utility by offering actionable, explainable insights for dermatological practice.

cs.CV↗

The smallest singular value of sparse discrete random matrices

Let $M_n$ be an $n \times n$ random matrix with i.i.d. sparse discrete entries. In this paper, we develop a simple framework to solve the approximate Spielman-Teng theorem for $M_n$, which has the following form: There exist constants $C, c>0$ such that for all $η\geq 0$, $\textbf{P}\left(s_n\left(M_n\right) \leq η\right) \lesssim n^C η+\exp \left(-n^c\right)$. As an application, we give an approximate Spielman-Teng theorem for $M_n$ whose entries are $μ-$lazy random variables, extending previous work by Tao and Vu.

math.PR↗