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We introduce the concept of data-driven finite element methods. These are finite-element discretizations of partial differential equations (PDEs) that resolve quantities of interest with striking accuracy, regardless of the underlying mesh…

Numerical Analysis · Mathematics 2022-11-15 Ignacio Brevis , Ignacio Muga , Kristoffer G. van der Zee

In this paper we revisit the classical Edge Disjoint Paths (EDP) problem, where one is given an undirected graph G and a set of terminal pairs P and asks whether G contains a set of pairwise edge-disjoint paths connecting every terminal…

Data Structures and Algorithms · Computer Science 2017-11-07 Robert Ganian , Sebastian Ordyniak , M. S. Ramanujan

As machine learning is increasingly used in essential systems, it is important to reduce or eliminate the incidence of serious bugs. A growing body of research has developed machine learning algorithms with formal guarantees about…

Machine Learning · Computer Science 2020-07-15 Jean-Baptiste Tristan , Joseph Tassarotti , Koundinya Vajjha , Michael L. Wick , Anindya Banerjee

Given a graph $G = (V,E)$, a subgraph $H$ is an \emph{additive $+\beta$ spanner} if $\dist_H(u,v) \le \dist_G(u,v) + \beta$ for all $u, v \in V$. A \emph{pairwise spanner} is a spanner for which the above inequality only must hold for…

Discrete Mathematics · Computer Science 2021-03-31 Reyan Ahmed , Greg Bodwin , Faryad Darabi Sahneh , Keaton Hamm , Stephen Kobourov , Richard Spence

Many fixed-parameter tractable algorithms using a bounded search tree have been repeatedly improved, often by describing a larger number of branching rules involving an increasingly complex case analysis. We introduce a novel and general…

Discrete Mathematics · Computer Science 2015-05-19 James Nastos , Yong Gao

Graph autoencoders (GAEs) are powerful tools in representation learning for graph embedding. However, the performance of GAEs is very dependent on the quality of the graph structure, i.e., of the adjacency matrix. In other words, GAEs would…

Machine Learning · Computer Science 2021-03-24 Rui Zhang , Yunxing Zhang , Xuelong Li

Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixedpoints of the belief propagation (BP) algorithm correspond to…

Machine Learning · Computer Science 2012-06-18 Tamir Hazan , Amnon Shashua

Positional Encodings (PEs) are essential for injecting structural information into Graph Neural Networks (GNNs), particularly Graph Transformers, yet their empirical impact remains insufficiently understood. We introduce a unified…

Machine Learning · Computer Science 2026-01-15 Florian Grötschla , Jiaqing Xie , Roger Wattenhofer

A vertex set $U \subseteq V$ of an undirected graph $G=(V,E)$ is a $\textit{resolving set}$ for $G$, if for every two distinct vertices $u,v \in V$ there is a vertex $w \in U$ such that the distances between $u$ and $w$ and the distance…

Computational Complexity · Computer Science 2018-06-28 Duygu Vietz , Stefan Hoffmann , Egon Wanke

In a celebrated work, Blais, Brody, and Matulef developed a technique for proving property testing lower bounds via reductions from communication complexity. Their work focused on testing properties of functions, and yielded new lower…

Computational Complexity · Computer Science 2018-01-26 Talya Eden , Will Rosenbaum

Treewidth is a parameter that emerged from the study of minor closed classes of graphs (i.e. classes closed under vertex and edge deletion, and edge contraction). It in some sense describes the global structure of a graph. Roughly, a graph…

Combinatorics · Mathematics 2022-02-02 Tara Abrishami , Maria Chudnovsky , Kristina Vušković

Due to the superior performance of Graph Neural Networks (GNNs) in various domains, there is an increasing interest in the GNN explanation problem "\emph{which fraction of the input graph is the most crucial to decide the model's…

Machine Learning · Computer Science 2022-07-04 Qinghua Zheng , Jihong Wang , Minnan Luo , Yaoliang Yu , Jundong Li , Lina Yao , Xiaojun Chang

Given a graph $G = (V,E)$, a threshold function $t~ :~ V \rightarrow \mathbb{N}$ and an integer $k$, we study the Harmless Set problem, where the goal is to find a subset of vertices $S \subseteq V$ of size at least $k$ such that every…

Computational Complexity · Computer Science 2022-01-27 Ajinkya Gaikwad , Soumen Maity

The theoretical models providing mathematical abstractions for several significant optimization problems in machine learning, combinatorial optimization, computer vision and statistical physics have intrinsic similarities. We propose a…

Data Structures and Algorithms · Computer Science 2018-04-18 Yi-Kai Wang

The last decade has seen a revival of interest in pebble games in the context of proof complexity. Pebbling has proven a useful tool for studying resolution-based proof systems when comparing the strength of different subsystems, showing…

Computational Complexity · Computer Science 2015-03-13 Jakob Nordström

We study the directed maximum common edge subgraph problem (DMCES) for the class of directed graphs that are finite, weakly connected, oriented, and simple. We use DMCES to define a metric on partially ordered sets that can be represented…

Data Structures and Algorithms · Computer Science 2020-12-07 Robert Nerem , Peter Crawford-Kahrl , Bree Cummins , Tomas Gedeon

An application area of vertex enumeration problem (VEP) is the usage within objective space based linear/convex {vector} optimization algorithms whose aim is to generate (an approximation of) the Pareto frontier. In such algorithms, VEP,…

Optimization and Control · Mathematics 2020-10-30 Irfan Caner Kaya , Firdevs Ulus

The Vertex Cover problem plays an essential role in the study of polynomial kernelization in parameterized complexity, i.e., the study of provable and efficient preprocessing for NP-hard problems. Motivated by the great variety of positive…

Computational Complexity · Computer Science 2019-05-10 Eva-Maria C. Hols , Stefan Kratsch , Astrid Pieterse

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

For a graph $G$, a function $\psi$ is called a \emph{bar visibility representation} of $G$ when for each vertex $v \in V(G)$, $\psi(v)$ is a horizontal line segment (\emph{bar}) and $uv \in E(G)$ iff there is an unobstructed, vertical,…

Computational Geometry · Computer Science 2021-12-17 Steven Chaplick , Grzegorz Guśpiel , Grzegorz Gutowski , Tomasz Krawczyk , Giuseppe Liotta