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Related papers: On largest volume simplices and sub-determinants

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In 2013, Koldobsky posed the problem to find a constant $d_n$, depending only on the dimension $n$, such that for any origin-symmetric convex body $K\subset\mathbb{R}^n$ there exists an $(n-1)$-dimensional linear subspace…

Metric Geometry · Mathematics 2024-01-26 Ansgar Freyer , Martin Henk

We develop a randomized approximation algorithm for the classical maximum coverage problem, which given a list of sets $A_1,A_2,\cdots, A_m$ and integer parameter $k$, select $k$ sets $A_{i_1}, A_{i_2},\cdots, A_{i_k}$ for maximum union…

Data Structures and Algorithms · Computer Science 2016-07-21 Bin Fu

We study the geometric knapsack problem in which we are given a set of $d$-dimensional objects (each with associated profits) and the goal is to find the maximum profit subset that can be packed non-overlappingly into a given…

Computational Geometry · Computer Science 2024-12-24 Pritam Acharya , Sujoy Bhore , Aaryan Gupta , Arindam Khan , Bratin Mondal , Andreas Wiese

There are two positive, absolute constants $c_{1}$ and $c_{2}$ so that the volume of the difference set of the $d$-dimensional Euclidean ball and an inscribed polytope with n vertices is larger than $$ c_{2}\ d\…

Metric Geometry · Mathematics 2008-02-03 Yehoram Gordon , Shlomo Reisner , Carsten Schütt

The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regev (2003) proved that the problem is NP-hard to approximate within a factor $2 - \epsilon$, assuming the Unique…

Computational Complexity · Computer Science 2015-11-30 Abbas Bazzi , Samuel Fiorini , Sebastian Pokutta , Ola Svensson

In the unsplittable flow problem on a path, we are given a capacitated path $P$ and $n$ tasks, each task having a demand, a profit, and start and end vertices. The goal is to compute a maximum profit set of tasks, such that for each edge…

Data Structures and Algorithms · Computer Science 2015-03-19 Paul Bonsma , Jens Schulz , Andreas Wiese

In this paper, we generalize the chance optimization problems and introduce constrained volume optimization where enables us to obtain convex formulation for challenging problems in systems and control. We show that many different problems…

Optimization and Control · Mathematics 2017-02-01 Ashkan Jasour , Constantino Lagoa

Coverings of convex bodies have emerged as a central component in the design of efficient solutions to approximation problems involving convex bodies. Intuitively, given a convex body $K$ and $\epsilon> 0$, a covering is a collection of…

Computational Geometry · Computer Science 2023-03-16 Sunil Arya , Guilherme D. da Fonseca , David M. Mount

Given a matrix $A \in \mathbb{R}^{m \times n}$ ($n$ vectors in $m$ dimensions), and a positive integer $k < n$, we consider the problem of selecting $k$ column vectors from $A$ such that the volume of the parallelepiped they define is…

Computational Complexity · Computer Science 2011-10-13 Ali Civril , Malik Magdon-Ismail

In the family of unit balls with constant volume we look at the ones whose algebraic representation has some extremal property. We consider the family of nonnegative homogeneous polynomials of even degree $d$ whose sublevel set $\G=\{\x:…

Optimization and Control · Mathematics 2014-08-21 Jean-Bernard Lasserre

Given $k$ collections of 2SAT clauses on the same set of variables $V$, can we find one assignment that satisfies a large fraction of clauses from each collection? We consider such simultaneous constraint satisfaction problems, and design…

Data Structures and Algorithms · Computer Science 2014-07-30 Amey Bhangale , Swastik Kopparty , Sushant Sachdeva

We give a polynomial-time approximation algorithm for the (not necessarily metric) $k$-Median problem. The algorithm is an $\alpha$-size-approximation algorithm for $\alpha < 1 + 2 \ln(n/k)$. That is, it guarantees a solution having size at…

Data Structures and Algorithms · Computer Science 2025-11-18 Neal E. Young

We show that a constant factor approximation of the shortest and closest lattice vector problem in any norm can be computed in time $2^{0.802\, n}$. This contrasts the corresponding $2^n$ time, (gap)-SETH based lower bounds for these…

Data Structures and Algorithms · Computer Science 2021-10-07 Thomas Rothvoss , Moritz Venzin

Recently, motivated by the rapid increase of the data size in various applications, Monemizadeh [APPROX'23] and Driemel, Monemizadeh, Oh, Staals, and Woodruff [SoCG'25] studied geometric problems in the setting where the only access to the…

Computational Geometry · Computer Science 2026-03-24 T. Schibler , J. Xue , J. Zhu

We consider the {\em Shaped Partition Problem} of partitioning $n$ given vectors in real $k$-space into $p$ parts so as to maximize an arbitrary objective function which is convex on the sum of vectors in each part, subject to arbitrary…

Combinatorics · Mathematics 2016-09-07 Frank K. Hwang , Shmuel Onn , Uriel G. Rothblum

In the course of classifying generic sparse polynomial systems which are solvable in radicals, Esterov recently showed that the volume of the Minkowski sum $P_1+\dots+P_d$ of $d$-dimensional lattice polytopes is bounded from above by a…

Metric Geometry · Mathematics 2020-12-22 Gennadiy Averkov , Christopher Borger , Ivan Soprunov

Submodular maximization generalizes many fundamental problems in discrete optimization, including Max-Cut in directed/undirected graphs, maximum coverage, maximum facility location and marketing over social networks. In this paper we…

Data Structures and Algorithms · Computer Science 2011-01-18 Ariel Kulik , Hadas Shachnai , Tami Tamir

Let $P$ be a set of $n$ points in the plane. We consider a variation of the classical Erd\H{o}s-Szekeres problem, presenting efficient algorithms with $O(n^3)$ running time and $O(n^2)$ space complexity that compute: (1) A subset $S$ of $P$…

Computational Geometry · Computer Science 2024-12-18 Hernán González-Aguilar , David Orden , Pablo Pérez-Lantero , David Rappaport , Carlos Seara , Javier Tejel , Jorge Urrutia

Given a hypothesis space, the large volume principle by Vladimir Vapnik prioritizes equivalence classes according to their volume in the hypothesis space. The volume approximation has hitherto been successfully applied to binary learning…

Machine Learning · Computer Science 2014-02-04 Gang Niu , Bo Dai , Marthinus Christoffel du Plessis , Masashi Sugiyama

Maximizing a submodular function is a fundamental task in machine learning and in this paper we study the deletion robust version of the problem under the classic matroids constraint. Here the goal is to extract a small size summary of the…

Data Structures and Algorithms · Computer Science 2025-05-26 Paul Dütting , Federico Fusco , Silvio Lattanzi , Ashkan Norouzi-Fard , Morteza Zadimoghaddam
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