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Given a plane graph $G$ (i.e., a planar graph with a fixed planar embedding) and a simple cycle $C$ in $G$ whose vertices are mapped to a convex polygon, we consider the question whether this drawing can be extended to a planar…

Computational Geometry · Computer Science 2013-08-16 Tamara Mchedlidze , Martin Nöllenburg , Ignaz Rutter

Network traffic matrix estimation is an ill-posed linear inverse problem: it requires to estimate the unobservable origin destination traffic flows, X, given the observable link traffic flows, Y, and a binary routing matrix, A, which are…

Networking and Internet Architecture · Computer Science 2021-12-20 Syed Muhammad Atif , Nicolas Gillis , Sameer Qazi , Imran Naseem

Computing the Euler genus of a graph is a fundamental problem in graph theory and topology. It has been shown to be NP-hard by [Thomassen '89] and a linear-time fixed-parameter algorithm has been obtained by [Mohar '99]. Despite extensive…

Data Structures and Algorithms · Computer Science 2014-12-05 Ken-ichi Kawarabayashi , Anastasios Sidiropoulos

We consider the problem of finding maximum flows in planar graphs with capacities on both vertices and edges and with multiple sources and sinks. We present three algorithms when the capacities are integers. The first algorithm runs in $O(n…

Data Structures and Algorithms · Computer Science 2021-05-26 Yipu Wang

We give a deterministic algorithm for finding the minimum (weight) cut of an undirected graph on $n$ vertices and $m$ edges using $\text{polylog}(n)$ calls to any maximum flow subroutine. Using the current best deterministic maximum flow…

Data Structures and Algorithms · Computer Science 2022-05-31 Jason Li , Debmalya Panigrahi

Community detection of network flows conventionally assumes one-step dynamics on the links. For sparse networks and interest in large-scale structures, longer timescales may be more appropriate. Oppositely, for large networks and interest…

Social and Information Networks · Computer Science 2016-03-22 Masoumeh Kheirkhahzadeh , Andrea Lancichinetti , Martin Rosvall

Beyond-planarity focuses on combinatorial properties of classes of non-planar graphs that allow for representations satisfying certain local geometric or topological constraints on their edge crossings. Beside the study of a specific graph…

Data Structures and Algorithms · Computer Science 2019-08-27 Patrizio Angelini , Michael A. Bekos , Michael Kaufmann , Thomas Schneck

To address the issue of computational efficiency related to the modelling of blood flow in complex networks, we derive a family of nonlinear lumped-parameter models for blood flow in compliant vessels departing from a well-established…

Numerical Analysis · Mathematics 2022-01-06 Beatrice Ghitti , Eleuterio F. Toro , Lucas O. Müller

We give an $O(n^{1.5} \log n)$ algorithm that, given a directed planar graph with arc capacities, a set of source nodes and a single sink node, finds a maximum flow from the sources to the sink . This is the first subquadratic-time strongly…

Data Structures and Algorithms · Computer Science 2010-09-15 Philip N. Klein , Shay Mozes

We present the first parallel fixed-parameter algorithm for subgraph isomorphism in planar graphs, bounded-genus graphs, and, more generally, all minor-closed graphs of locally bounded treewidth. Our randomized low depth algorithm has a…

Data Structures and Algorithms · Computer Science 2020-07-03 Lukas Gianinazzi , Torsten Hoefler

Optimal power flow (OPF) is a critical optimization problem that allocates power to the generators in order to satisfy the demand at a minimum cost. Solving this problem exactly is computationally infeasible in the general case. In this…

Systems and Control · Electrical Eng. & Systems 2022-10-18 Damian Owerko , Fernando Gama , Alejandro Ribeiro

Signal processing and machine learning algorithms for data supported over graphs, require the knowledge of the graph topology. Unless this information is given by the physics of the problem (e.g., water supply networks, power grids), the…

Signal Processing · Electrical Eng. & Systems 2021-02-11 Alberto Natali , Mario Coutino , Elvin Isufi , Geert Leus

Existing approaches for classifying dynamic graphs either lift graph kernels to the temporal domain, or use graph neural networks (GNNs). However, current baselines have scalability issues, cannot handle a changing node set, or do not take…

Machine Learning · Computer Science 2023-10-24 Franz Srambical , Bastian Rieck

Increased attention has been paid over the last four years to dynamic network embedding. Existing dynamic embedding methods, however, consider the problem as limited to the evolution of a topology over a sequence of global, discrete states.…

Machine Learning · Computer Science 2021-11-23 David Bayani

Input-output analysis of transitional channel flows has proven to be a valuable analytical tool for identifying important flow structures and energetic motions. The traditional approach abstracts the nonlinear terms as forcing that is…

Fluid Dynamics · Physics 2021-11-16 Chang Liu , Dennice F. Gayme

Estimation of latent network flows is a common problem in statistical network analysis. The typical setting is that we know the margins of the network, i.e. in- and outdegrees, but the flows are unobserved. In this paper, we develop a mixed…

Applications · Statistics 2020-01-23 Marc Schneble , Göran Kauermann

We show a deterministic constant-time local algorithm for constructing an approximately maximum flow and minimum fractional cut in multisource-multitarget networks with bounded degrees and bounded edge capacities. Locality means that the…

Data Structures and Algorithms · Computer Science 2023-11-03 Endre Csóka , András Pongrácz

We give a deterministic $m^{1+o(1)}$ time algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with $m$ edges and polynomially bounded integral demands, costs, and capacities. As a consequence, we obtain the…

Data Structures and Algorithms · Computer Science 2023-09-29 Jan van den Brand , Li Chen , Rasmus Kyng , Yang P. Liu , Richard Peng , Maximilian Probst Gutenberg , Sushant Sachdeva , Aaron Sidford

Graph filters are a staple tool for processing signals over graphs in a multitude of downstream tasks. However, they are commonly designed for graphs with a fixed number of nodes, despite real-world networks typically grow over time. This…

Machine Learning · Computer Science 2024-09-12 Bishwadeep Das , Elvin Isufi

We consider approximation algorithms for the problem of finding $x$ of minimal norm $\|x\|$ satisfying a linear system $\mathbf{A} x = \mathbf{b}$, where the norm $\|\cdot \|$ is arbitrary and generally non-Euclidean. We show a simple…

Data Structures and Algorithms · Computer Science 2016-06-28 Jonah Sherman