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We study the problem of approximating the eigenspectrum of a symmetric matrix $\mathbf A \in \mathbb{R}^{n \times n}$ with bounded entries (i.e., $\|\mathbf A\|_{\infty} \leq 1$). We present a simple sublinear time algorithm that…

Data Structures and Algorithms · Computer Science 2022-07-25 Rajarshi Bhattacharjee , Gregory Dexter , Petros Drineas , Cameron Musco , Archan Ray

Sublinear time algorithms for approximating maximum matching size have long been studied. Much of the progress over the last two decades on this problem has been on the algorithmic side. For instance, an algorithm of Behnezhad [FOCS'21]…

Data Structures and Algorithms · Computer Science 2022-11-30 Soheil Behnezhad , Mohammad Roghani , Aviad Rubinstein

We study the problem of estimating the size of the maximum matching in the sublinear-time setting. This problem has been extensively studied, with several known upper and lower bounds. A notable result by Behnezhad (FOCS 2021) established a…

Data Structures and Algorithms · Computer Science 2026-02-17 Vihan Shah

For a finite set $A\subset \mathbb{R}^d$, let $\Delta(A)$ denote the spread of $A$, which is the ratio of the maximum pairwise distance to the minimum pairwise distance. For a positive integer $n$, let $\gamma_d(n)$ denote the largest…

Combinatorics · Mathematics 2022-12-20 Adrian Dumitrescu , Csaba D. Tóth

We describe a randomized algorithm for producing a near-optimal hierarchical off-diagonal low-rank (HODLR) approximation to an $n\times n$ matrix $\mathbf{A}$, accessible only though matrix-vector products with $\mathbf{A}$ and…

Data Structures and Algorithms · Computer Science 2024-10-25 Tyler Chen , Feyza Duman Keles , Diana Halikias , Cameron Musco , Christopher Musco , David Persson

We give a proof of the conjecture of Nelson and Nguyen [FOCS 2013] on the optimal dimension and sparsity of oblivious subspace embeddings, up to sub-polylogarithmic factors: For any $n\geq d$ and $\epsilon\geq d^{-O(1)}$, there is a random…

Data Structures and Algorithms · Computer Science 2025-11-18 Shabarish Chenakkod , Michał Dereziński , Xiaoyu Dong

We study the problem of computing the $p\rightarrow q$ norm of a matrix $A \in R^{m \times n}$, defined as \[ \|A\|_{p\rightarrow q} ~:=~ \max_{x \,\in\, R^n \setminus \{0\}} \frac{\|Ax\|_q}{\|x\|_p} \] This problem generalizes the spectral…

Computational Complexity · Computer Science 2018-08-10 Vijay Bhattiprolu , Mrinalkanti Ghosh , Venkatesan Guruswami , Euiwoong Lee , Madhur Tulsiani

Estimating the discrepancy of the hypergraph of all arithmetic progressions in the set $[N]=\{1,2,\hdots,N\}$ was one of the famous open problems in combinatorial discrepancy theory for a long time. An extension of this classical hypergraph…

Number Theory · Mathematics 2007-05-23 Nils Hebbinghaus

We develop a topological framework for proving lower bounds on sign-rank via $\mathbb{Z}_2$-equivariant topology, and use it to resolve the sign-rank of the Gap Hamming Distance problem up to lower-order terms. For every (partial) sign…

Combinatorics · Mathematics 2026-04-14 Florian Frick , Kaave Hosseini , Aliaksei Vasileuski

Let $\gamma(S_n)$ be the minimum number of proper subgroups $H_i$ of the symmetric group $S_n$ such that each element in $S_n$ lies in some conjugate of one of the $H_i.$ In this paper we conjecture that…

Group Theory · Mathematics 2013-10-11 Daniela Bubboloni , Cheryl E. Praeger , Pablo Spiga

In this note, we propose a framework for proving computational lower bounds in norm approximation by leveraging a reverse detection--estimation gap. The starting point is a testing problem together with an estimator whose error is…

Statistics Theory · Mathematics 2026-04-07 Runshi Tang , Yuefeng Han , Anru R. Zhang

We establish sharp non-asymptotic probabilistic bounds for the star discrepancy of double-infinite random matrices -- a canonical model for sequences of random point sets in high dimensions. By integrating the recently proved…

Statistics Theory · Mathematics 2026-01-09 Xiaoda Xu , Jun Xian

We study the 'bad science matrix problem': among all matrices $A\in\mathbb{R}^{n\times n}$ whose rows have unit $\ell_2$-norm, determine the maximum of $\beta(A)=\frac{1}{2^n}\sum_{x\in\{\pm1\}^n}\|Ax\|_\infty$. Steinerberger [1]…

Functional Analysis · Mathematics 2025-09-16 Shridhar Sinha

We present the first sub-quadratic time algorithm that with high probability correctly reconstructs phylogenetic trees for short sequences generated by a Markov model of evolution. Due to rapid expansion in sequence databases, such very…

Populations and Evolution · Quantitative Biology 2012-06-01 Daniel G. Brown , Jakub Truszkowski

An oblivious subspace embedding is a random $m\times n$ matrix $\Pi$ such that, for any $d$-dimensional subspace, with high probability $\Pi$ preserves the norms of all vectors in that subspace within a $1\pm\epsilon$ factor. In this work,…

Data Structures and Algorithms · Computer Science 2025-04-30 Shabarish Chenakkod , Michał Dereziński , Xiaoyu Dong

We consider the problem of approximating the arboricity of a graph $G= (V,E)$, which we denote by $\mathsf{arb}(G)$, in sublinear time, where the arboricity of a graph is the minimal number of forests required to cover its edges. An…

Data Structures and Algorithms · Computer Science 2021-10-29 Talya Eden , Saleet Mossel , Dana Ron

Unbalanced translocations are among the most frequent chromosomal alterations, accounted for 30\% of all losses of heterozygosity, a major genetic event causing inactivation of tumor suppressor genes. Despite of their central role in…

Data Structures and Algorithms · Computer Science 2018-12-04 Domenico Cantone , Simone Faro , Arianna Pavone

Pattern matching can be used to calculate the support of patterns, and is a key issue in sequential pattern mining (or sequence pattern mining). Nonoverlapping pattern matching means that two occurrences cannot use the same character in the…

Databases · Computer Science 2022-09-08 Youxi Wu , Bojing Jian , Yan Li , He Jiang , Xindong Wu

In the numerical linear algebra community, it was suggested that to obtain nearly optimal bounds for various problems such as rank computation, finding a maximal linearly independent subset of columns (a basis), regression, or low-rank…

Data Structures and Algorithms · Computer Science 2021-11-04 Nadiia Chepurko , Kenneth L. Clarkson , Praneeth Kacham , David P. Woodruff

In the literature of high-dimensional central limit theorems, there is a gap between results for general limiting correlation matrix $\Sigma$ and the strongly non-degenerate case. For the general case where $\Sigma$ may be degenerate, under…

Probability · Mathematics 2023-05-30 Xiao Fang , Yuta Koike , Song-Hao Liu , Yi-Kun Zhao