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We present a brief structural equivalence between the symmetric TSP and a constrained Group Steiner Tree Problem (cGSTP) defined on a simplicial incidence graph. Given the complete weighted graph on the city set V, we form the bipartite…

Data Structures and Algorithms · Computer Science 2026-02-06 Yılmaz Arslanoğlu

We consider the well-studied problem of finding a spanning tree with minimum average distance between vertex pairs (called a MAD tree). This is a classic network design problem which is known to be NP-hard. While approximation algorithms…

Data Structures and Algorithms · Computer Science 2026-04-01 Tom-Lukas Breitkopf , Vincent Froese , Anton Herrmann , André Nichterlein , Camille Richer

Given a directed graph $G$ with arbitrary real-valued weights, the single source shortest-path problem (SSSP) asks for, given a source $s$ in $G$, finding a shortest path from $s$ to each vertex $v$ in $G$. A classical SSSP algorithm…

Data Structures and Algorithms · Computer Science 2019-03-06 Sanjiang Li , Yongming Li

We study Steiner Forest on $H$-subgraph-free graphs, that is, graphs that do not contain some fixed graph $H$ as a (not necessarily induced) subgraph. We are motivated by a recent framework that completely characterizes the complexity of…

Directed Steiner Tree (DST) is a central problem in combinatorial optimization and theoretical computer science: Given a directed graph $G=(V, E)$ with edge costs $c \in \mathbb{R}_{\geq 0}^E$, a root $r \in V$ and $k$ terminals $K\subseteq…

Data Structures and Algorithms · Computer Science 2020-04-28 Xiangyu Guo , Guy Kortsarz , Bundit Laekhanukit , Shi Li , Daniel Vaz , Jiayi Xian

The Steiner tree enumeration problem is a well known problem that asks for enumerating Steiner trees. Numerous theoretical works proposed algorithms for the problem and analyzed their complexity, but there are no practical algorithms and…

Data Structures and Algorithms · Computer Science 2021-04-20 Yuya Sasaki

We give a 1.25 approximation algorithm for the Steiner Tree Problem with distances one and two, improving on the best known bound for that problem.

Computational Complexity · Computer Science 2008-10-13 Piotr Berman , Marek Karpinski , Alex Zelikovsky

This paper focuses on finding a spanning tree of a graph to maximize the number of its internal vertices. We present an approximation algorithm for this problem which can achieve a performance ratio $\frac{4}{3}$ on undirected simple…

Data Structures and Algorithms · Computer Science 2014-09-15 Xingfu Li , Daming Zhu

The geometric bottleneck Steiner network problem on a set of vertices $X$ embedded in a normed plane requires one to construct a graph $G$ spanning $X$ and a variable set of $k\geq 0$ additional points, such that the length of the longest…

Combinatorics · Mathematics 2013-01-22 M. Brazil , C. J. Ras , D. A. Thomas

For a given graph $G=(V,\, E)$ with a terminal set $S$ and a selected root $r\in S$, a positive integer cost and a delay on every edge and a delay constraint $D\in Z^{+}$, the shallow-light Steiner tree (\emph{SLST}) problem is to compute a…

Data Structures and Algorithms · Computer Science 2013-09-04 Longkun Guo , Kewen Liao

Vertex deletion problems ask whether it is possible to delete at most $k$ vertices from a graph so that the resulting graph belongs to a specified graph class. Over the past years, the parameterized complexity of vertex deletion to a…

Data Structures and Algorithms · Computer Science 2017-08-07 Eduard Eiben , Robert Ganian , O-joung Kwon

Uniform cost-distance Steiner trees minimize the sum of the total length and weighted path lengths from a dedicated root to the other terminals. They are applied when the tree is intended for signal transmission, e.g. in chip design or…

Data Structures and Algorithms · Computer Science 2025-07-31 Josefine Foos , Stephan Held , Yannik Kyle Dustin Spitzley

We propose a Stein variational gradient descent method to concurrently sparsify, train, and provide uncertainty quantification of a complexly parameterized model such as a neural network. It employs a graph reconciliation and condensation…

Machine Learning · Computer Science 2024-12-24 Govinda Anantha Padmanabha , Cosmin Safta , Nikolaos Bouklas , Reese E. Jones

Stein Variational Gradient Descent (SVGD) is an algorithm for sampling from a target density which is known up to a multiplicative constant. Although SVGD is a popular algorithm in practice, its theoretical study is limited to a few recent…

Machine Learning · Computer Science 2022-06-20 Adil Salim , Lukang Sun , Peter Richtárik

We describe a technique to reorganize topologies of Steiner trees by exchanging neighbors of adjacent Steiner points. We explain how to use the systematic way of building trees, and therefore topologies, to find the correct topology after…

Data Structures and Algorithms · Computer Science 2018-03-13 Aymeric Grodet , Takuya Tsuchiya

We consider the classic problem of Network Reliability. A network is given together with a source vertex, one or more target vertices, and probabilities assigned to each of the edges. Each edge appears in the network with its associated…

Combinatorics · Mathematics 2019-03-20 Amir Kafshdar Goharshady , Fatemeh Mohammadi

We consider the problem of embedding the Steiner points of a Steiner tree with given topology into the rectilinear plane. Thereby, the length of the path between a distinguished terminal and each other terminal must not exceed given length…

Data Structures and Algorithms · Computer Science 2015-08-19 Jens Maßberg

Our main result is a full classification, for every connected graph $H$, of the computational complexity of Steiner Forest on $H$-subgraph-free graphs. To obtain this dichotomy, we establish the following new algorithmic, hardness, and…

Network design problems aim to compute low-cost structures such as routes, trees and subgraphs. Often, it is natural and desirable to require that these structures have small hop length or hop diameter. Unfortunately, optimization problems…

Data Structures and Algorithms · Computer Science 2020-11-13 Bernhard Haeupler , D Ellis Hershkowitz , Goran Zuzic

In this paper, we propose a physically inspired graph-theoretical clustering method, which first makes the data points organized into an attractive graph, called In-Tree, via a physically inspired rule, called Nearest Descent (ND). In…

Machine Learning · Computer Science 2018-01-26 Teng Qiu , Kaifu Yang , Chaoyi Li , Yongjie Li