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Let OT_d(n) be the smallest integer N such that every N-element point sequence in R^d in general position contains an order-type homogeneous subset of size n, where a set is order-type homogeneous if all (d+1)-tuples from this set have the…

Combinatorics · Mathematics 2014-01-14 Andrew Suk

For a field $\mathbb{F}$ and integers $d, k$ and $\ell$, a set $A \subseteq \mathbb{F}^d$ is called $(k,\ell)$-nearly orthogonal if all vectors in $A$ are non-self-orthogonal and every $k+1$ vectors in $A$ contain $\ell + 1$ pairwise…

Combinatorics · Mathematics 2025-05-30 Rajko Nenadov , Lander Verlinde

Quasi-convex optimization acts a pivotal part in many fields including economics and finance; the subgradient method is an effective iterative algorithm for solving large-scale quasi-convex optimization problems. In this paper, we…

Optimization and Control · Mathematics 2019-10-25 Yaohua Hu , Jiawen Li , Carisa Kwok Wai Yu

A famous result by Erd\H{o}s and Szekeres (1935) asserts that, for all $k,d \in \mathbb{N}$, there is a smallest integer $n = g^{(d)}(k)$ such that every set of at least $n$ points in $\mathbb{R}^d$ in general position contains a $k$-gon,…

Computational Geometry · Computer Science 2022-02-23 Manfred Scheucher

In an ordinary feature selection procedure, a set of important features is obtained by solving an optimization problem such as the Lasso regression problem, and we expect that the obtained features explain the data well. In this study,…

Machine Learning · Statistics 2018-10-16 Satoshi Hara , Takanori Maehara

$ \newcommand{\kalg}{{k_{\mathrm{alg}}}} \newcommand{\kopt}{{k_{\mathrm{opt}}}} \newcommand{\algset}{{T}} \renewcommand{\Re}{\mathbb{R}} \newcommand{\eps}{\varepsilon} \newcommand{\pth}[2][\!]{#1\left({#2}\right)} \newcommand{\npoints}{n}…

Computational Geometry · Computer Science 2017-07-04 Avrim Blum , Sariel Har-Peled , Benjamin Raichel

A monitoring edge-geodetic set of a graph is a subset $M$ of its vertices such that for every edge $e$ in the graph, deleting $e$ increases the distance between at least one pair of vertices in $M$. We study the following computational…

Computational Complexity · Computer Science 2025-05-27 Florent Foucaud , Clara Marcille , R. B. Sandeep , Sagnik Sen , S Taruni

We prove that any quasirandom uniform hypergraph $H$ can be approximately decomposed into any collection of bounded degree hypergraphs with almost as many edges. In fact, our results also apply to multipartite hypergraphs and even to the…

Combinatorics · Mathematics 2021-01-22 Stefan Ehard , Felix Joos

Traditionally, most complex intelligence architectures are extremely non-convex, which could not be well performed by convex optimization. However, this paper decomposes complex structures into three types of nodes: operators, algorithms…

Machine Learning · Computer Science 2018-01-16 Han Xiao

We show that large subsets of vector spaces over finite fields determine certain point configurations with prescribed distance structure. More specifically, we consider the complete graph with vertices as the points of $A \subseteq…

Combinatorics · Mathematics 2018-02-20 Alex Iosevich , Hans Parshall

A $k$-nearly independent vertex subset of a graph $G$ is a set of vertices that induces a subgraph containing exactly $k$ edges. For $k = 0$, this coincides with the classical notion of independent subsets. This paper investigates the…

Combinatorics · Mathematics 2025-10-29 Audace A. V. Dossou-Olory , Eric O. Andriantiana

Nearly convex sets play important roles in convex analysis, optimization and theory of monotone operators. We give a systematic study of nearly convex sets, and construct examples of subdifferentials of lower semicontinuous convex functions…

Optimization and Control · Mathematics 2015-07-28 Sarah M. Moffat , Walaa M. Moursi , Xianfu Wang

In a digraph, a quasi-kernel is a subset of vertices that is independent and such that every vertex can reach some vertex in that set via a directed path of length at most two. Whereas Chv\'atal and Lov\'asz proved in 1974 that every…

Discrete Mathematics · Computer Science 2021-07-09 Hélène Langlois , Frédéric Meunier , Romeo Rizzi , Stéphane Vialette

We show that one can define and effectively compute Stallings graphs for quasi-convex subgroups of automatic groups (\textit{e.g.} hyperbolic groups or right-angled Artin groups). These Stallings graphs are finite labeled graphs, which are…

Group Theory · Mathematics 2018-01-03 Olga Kharlampovich , Alexei Miasnikov , Pascal Weil

A coreset is a point set containing information about geometric properties of a larger point set. A series of previous works show that in many machine learning problems, especially in clustering problems, coreset could be very useful to…

Data Structures and Algorithms · Computer Science 2022-10-18 Yichuan Deng , Zhao Song , Yitan Wang , Yuanyuan Yang

Nonconvex sparse models have received significant attention in high-dimensional machine learning. In this paper, we study a new model consisting of a general convex or nonconvex objectives and a variety of continuous nonconvex…

Optimization and Control · Mathematics 2020-10-26 Digvijay Boob , Qi Deng , Guanghui Lan , Yilin Wang

We consider the problem of approximating the reachable set of a discrete-time polynomial system from a semialgebraic set of initial conditions under general semialgebraic set constraints. Assuming inclusion in a given simple set like a box…

Optimization and Control · Mathematics 2019-06-06 Victor Magron , Pierre-Loic Garoche , Didier Henrion , Xavier Thirioux

Friedman and Linial introduced the convex body chasing problem to explore the interplay between geometry and competitive ratio in metrical task systems. In convex body chasing, at each time step $t \in \mathbb{N}$, the online algorithm…

Data Structures and Algorithms · Computer Science 2018-11-16 C. J. Argue , Sébastien Bubeck , Michael B. Cohen , Anupam Gupta , Yin Tat Lee

Low congestion shortcuts, introduced by Ghaffari and Haeupler (SODA 2016), provide a unified framework for global optimization problems in the congest model of distributed computing. Roughly speaking, for a given graph $G$ and a collection…

Data Structures and Algorithms · Computer Science 2021-06-08 Shimon Kogan , Merav Parter

The discrepancy of a point set quantifies how well the points are distributed, with low-discrepancy point sets demonstrating exceptional uniform distribution properties. Such sets are integral to quasi-Monte Carlo methods, which approximate…

Number Theory · Mathematics 2026-02-16 Josef Dick , Takashi Goda , Gerhard Larcher , Friedrich Pillichshammer , Kosuke Suzuki
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