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We consider the problem $(\mathrm{P})$ of fitting $n$ standard Gaussian random vectors in $\mathbb{R}^d$ to the boundary of a centered ellipsoid, as $n, d \to \infty$. This problem is conjectured to have a sharp feasibility transition: for…

Probability · Mathematics 2024-10-03 Afonso S. Bandeira , Antoine Maillard , Shahar Mendelson , Elliot Paquette

Counting small patterns in a large dataset is a fundamental algorithmic task. The most common version of this task is subgraph/homomorphism counting, wherein we count the number of occurrences of a small pattern graph $H$ in an input graph…

Data Structures and Algorithms · Computer Science 2025-10-21 Daniel Paul-Pena , C. Seshadhri

The classic lower bound of Kuhn, Moscibroda and Wattenhofer [JACM 2016] states that approximate maximum matching and approximate vertex cover (among other problems) in the LOCAL model require $\Omega(\min\{\sqrt{\frac{\log n}{\log\log n}},…

Data Structures and Algorithms · Computer Science 2026-05-14 Peter Davies-Peck

In this article, we consider the Euclidean dispersion problems. Let $P=\{p_{1}, p_{2}, \ldots, p_{n}\}$ be a set of $n$ points in $\mathbb{R}^2$. For each point $p \in P$ and $S \subseteq P$, we define $cost_{\gamma}(p,S)$ as the sum of…

Computational Geometry · Computer Science 2021-05-20 Pawan K. Mishra , Gautam K. Das

We obtain tight lower bounds for the trace norm $\Vert \cdot \Vert_1$ of some matrices with diagonal zero, in terms of the entry-wise $L^1$-norm (denoted by $\Vert \cdot \Vert_{(1)}$). It is shown that on the space of nonzero real symmetric…

Spectral Theory · Mathematics 2023-10-24 Mostafa Einollahzadeh

We consider the problem of selecting the best subset of exactly $k$ columns from an $m \times n$ matrix $A$. We present and analyze a novel two-stage algorithm that runs in $O(\min\{mn^2,m^2n\})$ time and returns as output an $m \times k$…

Data Structures and Algorithms · Computer Science 2015-03-13 Christos Boutsidis , Michael W. Mahoney , Petros Drineas

We study the minimum \emph{Monitoring Edge Geodetic Set} (\megset) problem introduced in [Foucaud et al., CALDAM'23]: given a graph $G$, we say that an edge is monitored by a pair $u,v$ of vertices if \emph{all} shortest paths between $u$…

Data Structures and Algorithms · Computer Science 2025-10-09 Davide Bilò , Giordano Colli , Luca Forlizzi , Stefano Leucci

We present a randomized algorithm that computes a constant approximation of a graph's arboricity, using $\tilde{O}(n/\lambda)$ queries to adjacency lists and in the same time bound. Here, $n$ and $\lambda$ denote the number of nodes and the…

Data Structures and Algorithms · Computer Science 2025-12-23 Jiangqi Dai , Mohsen Ghaffari , Julian Portmann

The combinatorial discrepancy of arithmetic progressions inside $[N] := \{1, \ldots, N\}$ is the smallest integer $D$ for which $[N]$ can be colored with two colors so that any arithmetic progression in $[N]$ contains at most $D$ more…

Combinatorics · Mathematics 2026-01-27 Lily Li , Aleksandar Nikolov

We show a simple local norm regularization algorithm that works with high probability. Namely, we prove that if the entries of a $n \times n$ matrix $A$ are i.i.d. symmetrically distributed and have finite second moment, it is enough to…

Probability · Mathematics 2018-09-12 Elizaveta Rebrova

The $2 \rightarrow q$ norm of a matrix $X \in \mathbb{R}^{n \times d}$ is defined as $\lVert X \rVert_{2 \rightarrow q} = \sup_{\lVert v \rVert_2 = 1} \lVert Xv \rVert_q$. We give polynomial-time multiplicative approximation algorithms for…

Data Structures and Algorithms · Computer Science 2026-05-29 Samuel B. Hopkins , Stefan Tiegel

The radius and diameter are fundamental graph parameters. They are defined as the minimum and maximum of the eccentricities in a graph, respectively, where the eccentricity of a vertex is the largest distance from the vertex to another…

Data Structures and Algorithms · Computer Science 2015-06-08 Amir Abboud , Virginia Vassilevska Williams , Joshua Wang

We study the H^{-1}-norm of the function 1 on tubular neighbourhoods of curves in R^2. We take the limit of small thickness epsilon, and we prove two different asymptotic results. The first is an asymptotic development for a fixed curve in…

Analysis of PDEs · Mathematics 2019-07-11 Yves van Gennip , Mark A. Peletier

We study the connections between the notions of combinatorial discrepancy and graph degeneracy. In particular, we prove that the maximum discrepancy over all subgraphs $H$ of a graph $G$ of the neighborhood set system of $H$ is sandwiched…

Discrete Mathematics · Computer Science 2021-11-30 Mario Grobler , Yiting Jiang , Patrice Ossona de Mendez , Sebastian Siebertz , Alexandre Vigny

We introduce kernel thinning, a new procedure for compressing a distribution $\mathbb{P}$ more effectively than i.i.d. sampling or standard thinning. Given a suitable reproducing kernel $\mathbf{k}_{\star}$ and $O(n^2)$ time, kernel…

Machine Learning · Statistics 2024-05-14 Raaz Dwivedi , Lester Mackey

The L_2-discrepancy measures the irregularity of the distribution of a finite point set. In this note we prove lower bounds for the L_2 discrepancy of arbitrary N-point sets. Our main focus is on the two-dimensional case. Asymptotic upper…

Numerical Analysis · Mathematics 2014-02-19 Aicke Hinrichs , Lev Markhasin

We prove, using the subspace embedding guarantee in a black box way, that one can achieve the spectral norm guarantee for approximate matrix multiplication with a dimensionality-reducing map having $m = O(\tilde{r}/\varepsilon^2)$ rows.…

Data Structures and Algorithms · Computer Science 2016-03-03 Michael B. Cohen , Jelani Nelson , David P. Woodruff

We give an online algorithm and prove novel mistake and regret bounds for online binary matrix completion with side information. The mistake bounds we prove are of the form $\tilde{O}(D/\gamma^2)$. The term $1/\gamma^2$ is analogous to the…

Machine Learning · Computer Science 2020-05-18 Mark Herbster , Stephen Pasteris , Lisa Tse

Mordechay B. Levin has constructed a number $\lambda$ which is normal in base 2, and such that the sequence $(\left\{2^n \lambda\right\})_{n=0,1,2,\ldots}$ has very small discrepancy $D_N$. Indeed we have $N\cdot D_N = \mathcal{O}…

Number Theory · Mathematics 2022-11-09 Roswitha Hofer , Gerhard Larcher

For any $n>1$ and $0<\varepsilon<1/2$, we show the existence of an $n^{O(1)}$-point subset $X$ of $\mathbb{R}^n$ such that any linear map from $(X,\ell_2)$ to $\ell_2^m$ with distortion at most $1+\varepsilon$ must have $m = \Omega(\min\{n,…

Information Theory · Computer Science 2014-11-11 Kasper Green Larsen , Jelani Nelson