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In the present work, two machine learning based constitutive models for finite deformations are proposed. Using input convex neural networks, the models are hyperelastic, anisotropic and fulfill the polyconvexity condition, which implies…

Materials Science · Physics 2021-11-29 Dominik K. Klein , Mauricio Fernández , Robert J. Martin , Patrizio Neff , Oliver Weeger

Let $P$ be a convex polyhedron and $Q$ be a convex polygon with $n$ vertices in total in three-dimensional space. We present a deterministic algorithm that finds a translation vector $v \in \mathbb{R}^3$ maximizing the overlap area $|P \cap…

Computational Geometry · Computer Science 2025-01-28 Hyuk Jun Kweon , Honglin Zhu

Finite element methods usually construct basis functions and quadrature rules for multidimensional domains via tensor products of one-dimensional counterparts. While straightforward, this approach results in integration spaces larger than…

Numerical Analysis · Mathematics 2026-01-09 Tomas Teijeiro , Pouria Behnoudfar , Jamie M. Taylor , David Pardo , Victor M. Calo

Designing short DNA words is a problem of constructing a set (i.e., code) of n DNA strings (i.e., words) with the minimum length such that the Hamming distance between each pair of words is at least k and the n words satisfy a set of…

Data Structures and Algorithms · Computer Science 2012-02-01 Ming-Yang Kao , Henry C. M. Leung , He Sun , Yong Zhang

We study a $(1+\epsilon)$-approximate single-source shortest paths (henceforth, $(1+\epsilon)$-SSSP) in $n$-vertex undirected, weighted graphs in the parallel (PRAM) model of computation. A randomized algorithm with polylogarithmic time and…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-01 Elkin Michael , Matar Shaked

We present the first optimal randomized algorithm for constructing the order-$k$ Voronoi diagram of $n$ points in two dimensions. The expected running time is $O(n\log n + nk)$, which improves the previous, two-decades-old result of Ramos…

Computational Geometry · Computer Science 2023-10-25 Timothy M. Chan , Pingan Cheng , Da Wei Zheng

We study the two-dimensional geometric knapsack problem for convex polygons. Given a set of weighted convex polygons and a square knapsack, the goal is to select the most profitable subset of the given polygons that fits non-overlappingly…

Data Structures and Algorithms · Computer Science 2020-08-03 Arturo Merino , Andreas Wiese

Many existing algorithms for streaming geometric data analysis have been plagued by exponential dependencies in the space complexity, which are undesirable for processing high-dimensional data sets. In particular, once $d\geq\log n$, there…

Data Structures and Algorithms · Computer Science 2022-09-28 David P. Woodruff , Taisuke Yasuda

$\renewcommand{\Re}{\mathbb{R}}\newcommand{\eps}{{\varepsilon}}\newcommand{\poly}{\mathrm{poly}} $In this paper, we study the problem of $L_1$-fitting a shape to a set of $n$ points in $\Re^d$ (where $d$ is a fixed constant), where the…

Computational Geometry · Computer Science 2026-01-21 Sariel Har-Peled

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

Let $P$ be an orthogonal polygon of $n$ vertices, without holes. The Orthogonal Polygon Covering with Squares (OPCS) problem takes as input such an orthogonal polygon $P$ with integral vertex coordinates, and asks to find the minimum number…

Computational Geometry · Computer Science 2024-11-19 Anubhav Dhar , Subham Ghosh , Sudeshna Kolay

We consider the computational versions of the Erd\H os-Szekeres theorem and related problems in 3 dimensions. We show that, in constrast to the planar case, no polynomial time algorithm exists for determining the largest (empty) convex…

Computational Geometry · Computer Science 2011-11-28 Christian Knauer , Daniel Werner

Recent work has pinned down the existentially optimal size bounds for vertex fault-tolerant spanners: for any positive integer $k$, every $n$-node graph has a $(2k-1)$-spanner on $O(f^{1-1/k} n^{1+1/k})$ edges resilient to $f$ vertex…

Data Structures and Algorithms · Computer Science 2020-11-03 Greg Bodwin , Michael Dinitz , Caleb Robelle

A randomized algorithm for a search problem is *pseudodeterministic* if it produces a fixed canonical solution to the search problem with high probability. In their seminal work on the topic, Gat and Goldwasser posed as their main open…

Computational Complexity · Computer Science 2025-12-05 Lijie Chen , Zhenjian Lu , Igor C. Oliveira , Hanlin Ren , Rahul Santhanam

Vertex Subset Problems (VSPs) are a class of combinatorial optimization problems on graphs where the goal is to find a subset of vertices satisfying a predefined condition. Two prominent approaches for solving VSPs are dynamic programming…

Data Structures and Algorithms · Computer Science 2026-01-14 Mateus de Oliveira Oliveira , Wim Van den Broeck

Convex relaxations based on different hierarchies of linear/semi-definite programs have been used recently to devise approximation algorithms for various optimization problems. The approximation guarantee of these algorithms improves with…

Data Structures and Algorithms · Computer Science 2015-03-20 Venkatesan Guruswami , Ali Kemal Sinop

Let $ES_{d}(n)$ be the smallest integer such that any set of $ES_{d}(n)$ points in $\mathbb{R}^{d}$ in general position contains $n$ points in convex position. In 1960, Erd\H{o}s and Szekeres showed that $ES_{2}(n) \geq 2^{n-2} + 1$ holds,…

Combinatorics · Mathematics 2022-08-10 Cosmin Pohoata , Dmitrii Zakharov

We present a deterministic $(1+o(1))$-approximation $(n^{1/2+o(1)}+D^{1+o(1)})$-time algorithm for solving the single-source shortest paths problem on distributed weighted networks (the CONGEST model); here $n$ is the number of nodes in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-20 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

The $K$-medoids problem is a challenging combinatorial clustering task, widely used in data analysis applications. While numerous algorithms have been proposed to solve this problem, none of these are able to obtain an exact (globally…

Machine Learning · Computer Science 2024-05-22 Xi He , Max A. Little

We present a new approach to learning the structure and parameters of a Bayesian network based on regularized estimation in an exponential family representation. Here we show that, given a fixed variable order, the optimal structure and…

Machine Learning · Computer Science 2012-07-02 Yuhong Guo , Dale Schuurmans