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Optimal transport (OT) is a popular and powerful tool for comparing probability measures. However, OT suffers a few drawbacks: (i) input measures required to have the same mass, (ii) a high computational complexity, and (iii) indefiniteness…

Machine Learning · Computer Science 2023-02-27 Tam Le , Truyen Nguyen , Kenji Fukumizu

Distributed graph algorithms that separately optimize for either the number of rounds used or the total number of messages sent have been studied extensively. However, algorithms simultaneously efficient with respect to both measures have…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-18 Bernhard Haeupler , D. Ellis Hershkowitz , David Wajc

Recently there has been much interest in graph-based learning, with applications in collaborative filtering for recommender networks, link prediction for social networks and fraud detection. These networks can consist of millions of…

Social and Information Networks · Computer Science 2012-06-26 Purnamrita Sarkar , Andrew Moore

We propose a novel non-linear extension to the Orienteering Problem (OP), called the Correlated Orienteering Problem (COP). We use COP to model the planning of informative tours for the persistent monitoring of a spatiotemporal field with…

Robotics · Computer Science 2014-12-16 Jingjin Yu , Mac Schwager , Daniela Rus

A new conceptual foundation for the notion of "information" is proposed, based on the concept of a "distinction graph": a graph in which two nodes are connected iff they cannot be distinguished by a particular observer. The "graphtropy" of…

Artificial Intelligence · Computer Science 2019-02-05 Ben Goertzel

We consider the problem of clustering graph nodes over large-scale dynamic graphs, such as citation networks, images and web networks, when graph updates such as node/edge insertions/deletions are observed distributively. We propose…

Data Structures and Algorithms · Computer Science 2018-11-16 Chun Jiang Zhu , Tan Zhu , Kam-Yiu Lam , Song Han , Jinbo Bi

The study of the topological structure of complex networks has fascinated researchers for several decades, and today we have a fairly good understanding of the types and reoccurring characteristics of many different complex networks.…

Social and Information Networks · Computer Science 2014-06-23 Matthieu Roy , Stefan Schmid , Gilles Trédan

Modern transportation network modeling increasingly involves the integration of diverse methodologies including sensor-based forecasting, reinforcement learning, classical flow optimization, and demand modeling that have traditionally been…

Optimization and Control · Mathematics 2025-07-08 Xuesong , Zhou , Taehooie Kim , Mostafa Ameli , Henan , Zhu , Yu- dai Honma , Ram M. Pendyala

Mapping is crucial for spatial reasoning, planning and robot navigation. Existing approaches range from metric, which require precise geometry-based optimization, to purely topological, where image-as-node based graphs lack explicit…

Robotics · Computer Science 2024-05-10 Sourav Garg , Krishan Rana , Mehdi Hosseinzadeh , Lachlan Mares , Niko Sünderhauf , Feras Dayoub , Ian Reid

Schematic maps are in daily use to show the connectivity of subway systems and to facilitate travellers to plan their journeys effectively. This study surveys up-to-date algorithmic approaches in order to give an overview of the state of…

Physics and Society · Physics 2022-08-16 Hsiang-Yun Wu , Benjamin Niedermann , Shigeo Takahashi , Martin Nöllenburg

Continuous-time quantum walk describes the propagation of a quantum particle (or an excitation) evolving continuously in time on a graph. As such, it provides a natural framework for modeling transport processes, e.g., in light-harvesting…

Quantum Physics · Physics 2021-08-02 Luca Razzoli , Matteo G. A. Paris , Paolo Bordone

We give an algorithm to compute a morph between any two convex drawings of the same plane graph. The morph preserves the convexity of the drawing at any time instant and moves each vertex along a piecewise linear curve with linear…

Computational Geometry · Computer Science 2015-04-01 Patrizio Angelini , Giordano Da Lozzo , Fabrizio Frati , Anna Lubiw , Maurizio Patrignani , Vincenzo Roselli

Coordination graph is a promising approach to model agent collaboration in multi-agent reinforcement learning. It conducts a graph-based value factorization and induces explicit coordination among agents to complete complicated tasks.…

Machine Learning · Computer Science 2022-09-20 Qianlan Yang , Weijun Dong , Zhizhou Ren , Jianhao Wang , Tonghan Wang , Chongjie Zhang

The development of vehicle-to-vehicle (V2V) communication facil-itates the study of cooperative positioning (CP) techniques for vehicular applications. The CP methods can improve the posi-tioning availability and accuracy by inter-vehicle…

Robotics · Computer Science 2023-10-11 Chen Zhuang , Hongbo Zhao

Constructing appropriate representations of molecules lies at the core of numerous tasks such as material science, chemistry and drug designs. Recent researches abstract molecules as attributed graphs and employ graph neural networks (GNN)…

Machine Learning · Computer Science 2021-07-29 Jianwen Chen , Shuangjia Zheng , Ying Song , Jiahua Rao , Yuedong Yang

In this paper, we present an approach to enhance and improve the current normal map rendering technique. Our algorithm is based on semi-discrete Optimal Mass Transportation (OMT) theory and has a solid theoretical base. The key difference…

Graphics · Computer Science 2020-04-22 Hui Zhao , Kehua Su , Ming Ma , Na Lei , Li Cui , Xianfeng Gu

This article gives an introduction to optimal transport, a mathematical theory that makes it possible to measure distances between functions (or distances between more general objects), to interpolate between objects or to enforce…

Analysis of PDEs · Mathematics 2017-10-10 Bruno Levy , Erica Schwindt

We study a large family of graph covering problems, whose definitions rely on distances, for graphs of bounded cyclomatic number (that is, the minimum number of edges that need to be removed from the graph to destroy all cycles). These…

Discrete Mathematics · Computer Science 2025-09-03 Dibyayan Chakraborty , Florent Foucaud , Anni Hakanen

Optimal transport (OT) theory describes general principles to define and select, among many possible choices, the most efficient way to map a probability measure onto another. That theory has been mostly used to estimate, given a pair of…

Machine Learning · Computer Science 2023-04-03 Charlotte Bunne , Andreas Krause , Marco Cuturi

Autonomous vehicles navigate in dynamically changing environments under a wide variety of conditions, being continuously influenced by surrounding objects. Modelling interactions among agents is essential for accurately forecasting other…

Machine Learning · Computer Science 2021-06-01 Sandra Carrasco , David Fernández Llorca , Miguel Ángel Sotelo