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Hyperbolic-parabolic partial differential equations are widely used for the modeling of complex, multiscale problems. High-order methods such as the discontinuous Galerkin (DG) scheme are attractive candidates for their numerical…

Numerical Analysis · Mathematics 2025-07-08 Jens Keim , Anna Schwarz , Patrick Kopper , Marcel Blind , Christian Rohde , Andrea Beck

The aim of this paper is to apply a high-order discontinuous-in-time scheme to second-order hyperbolic partial differential equations (PDEs). We first discretize the PDEs in time while keeping the spatial differential operators…

Numerical Analysis · Mathematics 2021-11-30 Aili Shao

The Stein Variational Gradient Descent method is a variational inference method in statistics that has recently received a lot of attention. The method provides a deterministic approximation of the target distribution, by introducing a…

Analysis of PDEs · Mathematics 2024-12-16 José A. Carrillo , Jakub Skrzeczkowski , Jethro Warnett

We study the hyperbolic random geometric graph introduced in Krioukov et al. For a sequence $R_n \to \infty$, we define these graphs to have the vertex set as Poisson points distributed uniformly in balls $B(0,R_n) \subset B_d^{\alpha}$,…

Probability · Mathematics 2018-02-20 Takashi Owada , D. Yogeshwaran

Learning the representation of data with hierarchical structures in the hyperbolic space attracts increasing attention in recent years. Due to the constant negative curvature, the hyperbolic space resembles tree metrics and captures the…

Machine Learning · Computer Science 2022-02-21 Huiru Xiao , Caigao Jiang , Yangqiu Song , James Zhang , Junwu Xiong

Hyperbolic machine learning is an emerging field aimed at representing data with a hierarchical structure. However, there is a lack of tools for evaluation and analysis of the resulting hyperbolic data representations. To this end, we…

Fast exact algorithms are known for Hamiltonian paths in undirected and directed bipartite graphs through elegant though involved algorithms that are quite different from each other. We devise algorithms that are simple and similar to each…

Data Structures and Algorithms · Computer Science 2025-12-10 V. Arvind , Srijan Chakraborty , Samir Datta , Asif Khan

We derive and analyze a hybridizable discontinuous Galerkin (HDG) method for approximating weak solutions to the equations of time-harmonic linear elasticity on a bounded Lipschitz domain in three dimensions. The real symmetry of the stress…

Numerical Analysis · Mathematics 2016-11-18 Allan Hungria , Daniele Prada , Francisco-Javier Sayas

In $d$-Scattered Set we are given an (edge-weighted) graph and are asked to select at least $k$ vertices, so that the distance between any pair is at least $d$, thus generalizing Independent Set. We provide upper and lower bounds on the…

Computational Complexity · Computer Science 2018-11-13 Ioannis Katsikarelis , Michael Lampis , Vangelis Th. Paschos

Given a set $P$ of $n$ points in $\mathbb{R}^2$ and an input line $\gamma$ in $\mathbb{R}^2$, we present an algorithm that runs in optimal $\Theta(n\log n)$ time and $\Theta(n)$ space to solve a restricted version of the $1$-Steiner tree…

Computational Geometry · Computer Science 2023-06-16 Prosenjit Bose , Anthony D'Angelo , Stephane Durocher

Makespan scheduling on identical machines is one of the most basic and fundamental packing problems studied in the discrete optimization literature. It asks for an assignment of $n$ jobs to a set of $m$ identical machines that minimizes the…

Data Structures and Algorithms · Computer Science 2016-04-26 Klaus Jansen , Kim-Manuel Klein , José Verschae

Building trees to represent or to fit distances is a critical component of phylogenetic analysis, metric embeddings, approximation algorithms, geometric graph neural nets, and the analysis of hierarchical data. Much of the previous…

Data Structures and Algorithms · Computer Science 2024-09-04 Joon-Hyeok Yim , Anna C. Gilbert

The VertexCover problem is proven to be computationally hard in different ways: It is NP-complete to find an optimal solution and even NP-hard to find an approximation with reasonable factors. In contrast, recent experiments suggest that on…

Data Structures and Algorithms · Computer Science 2020-02-20 Thomas Bläsius , Philipp Fischbeck , Tobias Friedrich , Maximilian Katzmann

The hop-constrained Steiner tree problem (HSTP) is a generalization of the classical Steiner tree problem. It asks for a minimum cost subtree that spans some specified nodes of a given graph, such that the number of edges between each node…

Data Structures and Algorithms · Computer Science 2021-11-16 Adalat Jabrayilov

In this paper we design and prove correct a fully dynamic distributed algorithm for maintaining an approximate Steiner tree that connects via a minimum-weight spanning tree a subset of nodes of a network (referred as Steiner members or…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-13 Lélia Blin , Maria Gradinariu Potop-Butucaru , Stephane Rovedakis

We give new sublinear and parallel algorithms for the extensively studied problem of approximating n-variable r-CSPs (constraint satisfaction problems with constraints of arity r up to an additive error. The running time of our algorithms…

Data Structures and Algorithms · Computer Science 2014-07-31 Grigory Yaroslavtsev

In this experimental study we consider Steiner tree approximations that guarantee a constant approximation of ratio smaller than $2$. The considered greedy algorithms and approaches based on linear programming involve the incorporation of…

Data Structures and Algorithms · Computer Science 2015-12-10 Stephan Beyer , Markus Chimani

We present a new approximation algorithm for the treewidth problem which finds an upper bound on the treewidth and constructs a corresponding tree decomposition as well. Our algorithm is a faster variation of Reed's classical algorithm. For…

Data Structures and Algorithms · Computer Science 2022-06-24 Mahdi Belbasi , Martin Fürer

We introduce a framework for analyzing topological tipping in time-evolutionary point clouds by extending the recently proposed Topological Optimal Transport (TpOT) distance. While TpOT unifies geometric, homological, and higher-order…

Machine Learning · Statistics 2026-03-18 Yixin Wang , Ting Gao , Jinqiao Duan

Hyperbolic space naturally encodes hierarchical structures such as phylogenies (binary trees), where inward-bending geodesics reflect paths through least common ancestors, and the exponential growth of neighborhoods mirrors the…

Machine Learning · Computer Science 2025-07-17 Alex Chen , Philipe Chlenski , Kenneth Munyuza , Antonio Khalil Moretti , Christian A. Naesseth , Itsik Pe'er
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