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Tensor network contraction is a fundamental mathematical operation that generalizes the dot product and matrix multiplication. It finds applications in numerous domains, such as database systems, graph theory, machine learning, probability…

Data Structures and Algorithms · Computer Science 2026-03-10 Mike Heddes , Igor Nunes , Tony Givargis , Alex Nicolau

We map the conformation space of a simple lattice polymer chain to a network, where (i) the vertices of the network have a one-to-one correspondence to the conformations of the chain, and (ii) a link between two vertices indicates the…

Soft Condensed Matter · Physics 2009-10-31 A. Scala , L. A. N. Amaral , M. Barthelemy

In this paper, we formulate a simple algorithm that detects contours around a region of interest in an image. After an initial smoothing, the method is based on viewing an image as a topographic surface and finding convex and/or concave…

Image and Video Processing · Electrical Eng. & Systems 2019-05-31 Victor Churchill

As supported by abundant experimental evidence, neural networks are state-of-the-art for many approximation tasks in high-dimensional spaces. Still, there is a lack of a rigorous theoretical understanding of what they can approximate, at…

Numerical Analysis · Mathematics 2024-06-24 Elena Celledoni , James Jackaman , Davide Murari , Brynjulf Owren

Random networks are increasingly used to analyse complex transportation networks, such as airline routes, roads and rail networks. So far, this research has been focused on describing the properties of the networks with the help of random…

Physics and Society · Physics 2017-09-19 Jürgen Hackl , Bryan T. Adey

The shortest path problem is among the most fundamental combinatorial optimization problems to answer reachability queries. It is hard to deter-mine which vertices or edges are visited during shortest path traversals. In this paper, we…

Social and Information Networks · Computer Science 2014-12-30 Waqas Nawaz , Kifayat Ullah Khan , Young-Koo Lee

The graph is one of the most widely used mathematical structures in engineering and science because of its representational power and inherent ability to demonstrate the relationship between objects. The objective of this work is to…

Data Structures and Algorithms · Computer Science 2021-01-01 Shri Prakash Dwivedi

One abstract method for the study of network transportation is proposed in this paper. By interpolating the properties of the edges that constitute network into the two leading parameters of the nodes, this method can abstract the…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Chang Yun-Feng , Xu Cai

Magnitude pruning is one of the mainstream methods in lightweight architecture design whose goal is to extract subnetworks with the largest weight connections. This method is known to be successful, but under very high pruning regimes, it…

Computer Vision and Pattern Recognition · Computer Science 2023-07-03 Hichem Sahbi

The visibility graph of a simple polygon represents visibility relations between its vertices. Knowing the correct order of the vertices around the boundary of a polygon and its visibility graph, it is an open problem to locate the vertices…

Computational Geometry · Computer Science 2019-05-03 Sahar Mehrpour , Alireza Zarei

In this paper, we introduced a novel approach to computing the fewest-turn map directions or routes based on the concept of natural roads. Natural roads are joined road segments that perceptually constitute good continuity. This approach…

Computational Geometry · Computer Science 2013-07-17 Bin Jiang , Xintao Liu

A $\textit{polygonal curve}$ is a collection of $m$ connected line segments specified as the linear interpolation of a list of points $\{p_0, p_1, \ldots, p_m\}$. These curves may be obtained by sampling points from an oriented curve in…

Numerical Analysis · Mathematics 2021-09-10 Marcella Manivel , Milena Silva , Robert Thompson

While most state-of-the-art instance segmentation methods produce binary segmentation masks, geographic and cartographic applications typically require precise vector polygons of extracted objects instead of rasterized output. This paper…

Computer Vision and Pattern Recognition · Computer Science 2022-04-07 Stefano Zorzi , Shabab Bazrafkan , Stefan Habenschuss , Friedrich Fraundorfer

In this paper we introduce min-plus low rank matrix approximation. By using min and plus rather than plus and times as the basic operations in the matrix multiplication; min-plus low rank matrix approximation is able to detect…

Numerical Analysis · Mathematics 2017-08-23 James Hook

The use of complex networks as a modern approach to understanding the world and its dynamics is well-established in literature. The adjacency matrix, which provides a one-to-one representation of a complex network, can also yield several…

Social and Information Networks · Computer Science 2023-01-23 Mariane B. Neiva , Odemir M. Bruno

Large graphs are difficult to represent, visualize, and understand. In this paper, we introduce "gate graph" - a new approach to perform graph simplification. A gate graph provides a simplified topological view of the original graph.…

Social and Information Networks · Computer Science 2016-11-18 Ning Ruan , Ruoming Jin , Yan Huang

A path or a polygonal domain is C-oriented if the orientations of its edges belong to a set of C given orientations; this is a generalization of the notable rectilinear case (C = 2). We study exact and approximation algorithms for…

Computational Geometry · Computer Science 2013-02-14 Joseph S. B. Mitchell , Valentin Polishchuk , Mikko Sysikaski

Networks are important representations in computer science to communicate structural aspects of a given system of interacting components. The evolution of a network has several topological properties that can provide us information on the…

Social and Information Networks · Computer Science 2020-04-30 Joao Pita Costa , Tihana Galinac Grbac

Computing shortest path distances between nodes lies at the heart of many graph algorithms and applications. Traditional exact methods such as breadth-first-search (BFS) do not scale up to contemporary, rapidly evolving today's massive…

Machine Learning · Computer Science 2020-02-14 Fatemeh Salehi Rizi , Joerg Schloetterer , Michael Granitzer

In this work, Transition Probability Matrix (TPM) is proposed as a new method for extracting the features of nodes in the graph. The proposed method uses random walks to capture the connectivity structure of a node's close neighborhood. The…

Machine Learning · Computer Science 2023-03-07 Sarmad N. Mohammed , Semra Gündüç