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The graph layouts used for complex network studies have been mainly been developed to improve visualization. If we interpret the layouts in metric spaces such as Euclidean ones, however, the embedded spatial information can be a valuable…

Physics and Society · Physics 2012-12-19 Sang Hoon Lee , Petter Holme

We propose a dynamical process for network evolution, aiming at explaining the emergence of the small world phenomenon, i.e., the statistical observation that any pair of individuals are linked by a short chain of acquaintances computable…

Data Structures and Algorithms · Computer Science 2008-03-04 Augustin Chaintreau , Pierre Fraigniaud , Emmanuelle Lebhar

Human navigation has been of interest to psychologists and cognitive scientists since the past few decades. It was in the recent past that a study of human navigational strategies was initiated with a network analytic approach, instigated…

Data Structures and Algorithms · Computer Science 2013-05-08 Rishi Ranjan Singh , Shreyas Balakuntala , Sudarshan Iyengar

Understanding the mechanisms of neural communication in large-scale brain networks remains a major goal in neuroscience. We investigated whether navigation is a parsimonious routing model for connectomics. Navigating a network involves…

Neurons and Cognition · Quantitative Biology 2018-06-05 Caio Seguin , Martijn P. van den Heuvel , Andrew Zalesky

Today's networks consist of many autonomous entities that follow their own objectives, i.e., smart devices or parts of large AI systems, that are interconnected. Given the size and complexity of most communication networks, each entity…

Computer Science and Game Theory · Computer Science 2026-02-02 Pascal Lenzner , Paraskevi Machaira

As a vital cognitive function of animals, the navigation skill is first built on the accurate perception of the directional heading in the environment. Head direction cells (HDCs), found in the limbic system of animals, are proven to play…

Neural and Evolutionary Computing · Computer Science 2021-09-23 Zhenshan Bing , Amir EI Sewisy , Genghang Zhuang , Florian Walter , Fabrice O. Morin , Kai Huang , Alois Knoll

Greedy embedding (or drawing) is a simple and efficient strategy to route messages in wireless sensor networks. For each source-destination pair of nodes s, t in a greedy embedding there is always a neighbor u of s that is closer to t…

Computational Geometry · Computer Science 2013-06-24 Martin Nöllenburg , Roman Prutkin

In this paper, we design a greedy routing on networks of mobile agents. In the greedy routing algorithm, every time step a packet in agent $i$ is delivered to the agent $j$ whose distance from the destination is shortest among searched…

Networking and Internet Architecture · Computer Science 2011-12-21 Han-Xin Yang , Wen-Xu Wang , Ying-Cheng Lai , Bing-Hong Wang

Human navigation has been a topic of interest in spatial cognition from the past few decades. It has been experimentally observed that humans accomplish the task of way-finding a destination in an unknown environment by recognizing…

Social and Information Networks · Computer Science 2011-11-22 Vijesh M. , Sudarshan Iyengar , Vijay Mahantesh , Amitash Ramesh , Veni Madhavan

A drawing of a graph is greedy if for each ordered pair of vertices u and v, there is a path from u to v such that the Euclidean distance to v decreases monotonically at every vertex of the path. The existence of greedy drawings has been…

Random scale-free networks are ultrasmall worlds. The average length of the shortest paths in networks of size N scales as lnlnN. Here we show that these ultrasmall worlds can be navigated in ultrashort time. Greedy routing on scale-free…

Disordered Systems and Neural Networks · Physics 2009-02-08 Marian Boguna , Dmitri Krioukov

We analyze greedy routing in a random graph G_n constructed on the vertex set V = {1, 2, ..., n} embedded in Z. Vertices are inserted according to a uniform random permutation pi, and each newly inserted vertex connects to its nearest…

Combinatorics · Mathematics 2026-04-22 Alexander Ponomarenko

We consider the problem of searching for a node on a labelled random graph according to a greedy algorithm that selects a route to the desired node using metric information on the graph. Motivated by peer-to-peer networks two types of…

Statistical Mechanics · Physics 2013-05-29 David Lancaster

We show that complex (scale-free) network topologies naturally emerge from hyperbolic metric spaces. Hyperbolic geometry facilitates maximally efficient greedy forwarding in these networks. Greedy forwarding is topology-oblivious.…

Statistical Mechanics · Physics 2010-09-13 Fragkiskos Papadopoulos , Dmitri Krioukov , Marian Boguna , Amin Vahdat

Geographic routing with greedy relaying strategies have been widely studied as a routing scheme in sensor networks. These schemes assume that the nodes have perfect information about the location of the destination. When the distance…

Information Theory · Computer Science 2007-07-13 Sundar Subramanian , Sanjay Shakkottai

We present a greedy-based approach to construct an efficient single hidden layer neural network with the ReLU activation that approximates a target function. In our approach we obtain a shallow network by utilizing a greedy algorithm with…

Machine Learning · Computer Science 2021-10-01 Anton Dereventsov , Armenak Petrosyan , Clayton Webster

Core-periphery structure is a common property of complex networks, which is a composition of tightly connected groups of core vertices and sparsely connected periphery vertices. This structure frequently emerges in traffic systems, biology,…

Social and Information Networks · Computer Science 2019-05-28 Junteng Jia , Austin R. Benson

We present a novel geographical routing scheme for spontaneous wireless mesh networks. Greedy geographical routing has many advantages, but suffers from packet losses occurring at the border of voids. In this paper, we propose a flexible…

Networking and Internet Architecture · Computer Science 2009-02-25 Fabrice Theoleyre , Eryk Schiller , Andrzej Duda

Hippocampal neurons track positions of self, others, and gaze direction. However, it is unclear how their respective neural codes differ enough to avoid confusion while allowing for abstraction. We recorded from populations of hippocampal…

The ubiquity of large-scale graphs in node-classification tasks significantly hinders the real-world applications of Graph Neural Networks (GNNs). Node sampling, graph coarsening, and dataset condensation are effective strategies for…

Machine Learning · Computer Science 2024-05-28 Mucong Ding , Yinhan He , Jundong Li , Furong Huang