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Graph Neural Networks (GNNs) have received considerable attention on graph-structured data learning for a wide variety of tasks. The well-designed propagation mechanism which has been demonstrated effective is the most fundamental part of…

Machine Learning · Computer Science 2021-01-29 Meiqi Zhu , Xiao Wang , Chuan Shi , Houye Ji , Peng Cui

Functional 3D scene graphs offer a versatile and flexible representation for 3D scene understanding and robotic manipulation, defined by object nodes, interactive elements, and functional relationship edges. However, their potential remains…

The clustering method based on graph models has garnered increased attention for its widespread applicability across various knowledge domains. Its adaptability to integrate seamlessly with other relevant applications endows the graph…

Machine Learning · Computer Science 2025-04-02 Xinrun Xu , Manying Lv , Zhanbiao Lian , Yurong Wu , Jin Yan , Shan Jiang , Zhiming Ding

Hypergraph visualization has many applications in network data analysis. Recently, a polygon-based representation for hypergraphs has been proposed with demonstrated benefits. However, the polygon-based layout often suffers from excessive…

Graphics · Computer Science 2023-08-10 Peter Oliver , Eugene Zhang , Yue Zhang

Driven by many applications in graph analytics, the problem of computing $k$-edge connected components ($k$-ECCs) of a graph $G$ for a user-given $k$ has been extensively studied recently. In this paper, we investigate the problem of…

Data Structures and Algorithms · Computer Science 2017-11-29 Lijun Chang

In this paper, we discuss how to design the graph topology to reduce the communication complexity of certain algorithms for decentralized optimization. Our goal is to minimize the total communication needed to achieve a prescribed accuracy.…

Optimization and Control · Mathematics 2016-12-06 Yat-Tin Chow , Wei Shi , Tianyu Wu , Wotao Yin

Many numerical methods for evaluating matrix functions can be naturally viewed as computational graphs. Rephrasing these methods as directed acyclic graphs (DAGs) is a particularly effective approach to study existing techniques, improve…

Numerical Analysis · Mathematics 2021-08-20 Elias Jarlebring , Massimiliano Fasi , Emil Ringh

Scene graphs represent the key components of a scene in a compact and semantically rich way, but are difficult to build during incremental SLAM operation because of the challenges of robustly identifying abstract scene elements and…

Computer Vision and Pattern Recognition · Computer Science 2022-04-06 Joseph Ortiz , Talfan Evans , Edgar Sucar , Andrew J. Davison

A \emph{$t$-treewidth-modulator} of a graph $G$ is a set $X \subseteq V(G)$ such that the treewidth of $G-X$ is at most some constant $t-1$. In this paper, we present a novel algorithm to compute a decomposition scheme for graphs $G$ that…

Data Structures and Algorithms · Computer Science 2012-08-02 Eun Jung Kim , Alexander Langer , Christophe Paul , Felix Reidl , Peter Rossmanith , Ignasi Sau , Somnath Sikdar

To cope with the intractability of answering Conjunctive Queries (CQs) and solving Constraint Satisfaction Problems (CSPs), several notions of hypergraph decompositions have been proposed -- giving rise to different notions of width,…

Databases · Computer Science 2020-09-04 Wolfgang Fischl , Georg Gottlob , Davide Mario Longo , Reinhard Pichler

Separated graphs provide a powerful combinatorial tool for approximating dynamical systems. This paper details the explicit construction of Bratteli-like separated graphs -- a generalization of classical Bratteli diagrams -- that encode the…

Dynamical Systems · Mathematics 2026-03-17 Joan Claramunt

Transmission line failures in power systems propagate and cascade non-locally. This well-known yet counter-intuitive feature makes it even more challenging to optimally and reliably operate these complex networks. In this work we present a…

Optimization and Control · Mathematics 2021-05-12 Alessandro Zocca , Chen Liang , Linqi Guo , Steven H. Low , Adam Wierman

Graph Neural Networks (GNNs) draw their strength from explicitly modeling the topological information of structured data. However, existing GNNs suffer from limited capability in capturing the hierarchical graph representation which plays…

Machine Learning · Computer Science 2021-03-30 Jinyu Yang , Peilin Zhao , Yu Rong , Chaochao Yan , Chunyuan Li , Hehuan Ma , Junzhou Huang

Large language models (LLMs) have shown promise in table Question Answering (Table QA). However, extending these capabilities to multi-table QA remains challenging due to unreliable schema linking across complex tables. Existing methods…

Artificial Intelligence · Computer Science 2025-11-25 Xixi Wang , Miguel Costa , Jordanka Kovaceva , Shuai Wang , Francisco C. Pereira

In this paper we present an algorithmic framework for solving a class of combinatorial optimization problems on graphs with bounded pathwidth. The problems are NP-hard in general, but solvable in linear time on this type of graphs. The…

Data Structures and Algorithms · Computer Science 2012-12-18 Mugurel Ionut Andreica

This paper studies how utility graphs decomposition algorithms can be used to effectively search for Pareto-efficient outcomes in complex automated negotiation. We propose a number of algorithms that can efficiently handle high-dimensional…

Multiagent Systems · Computer Science 2025-10-10 Valentin Robu , Mark Klein

The 'exact subgraph' approach was recently introduced as a hierarchical scheme to get increasingly tight semidefinite programming relaxations of several NP-hard graph optimization problems. Solving these relaxations is a computational…

Optimization and Control · Mathematics 2019-08-09 Elisabeth Gaar , Franz Rendl

To cope with the intractability of answering Conjunctive Queries (CQs) and solving Constraint Satisfaction Problems (CSPs), several notions of hypergraph decompositions have been proposed -- giving rise to different notions of width,…

Databases · Computer Science 2018-11-21 Wolfgang Fischl , Georg Gottlob , Davide M. Longo , Reinhard Pichler

We state a combinatorial optimization problem whose feasible solutions define both a decomposition and a node labeling of a given graph. This problem offers a common mathematical abstraction of seemingly unrelated computer vision tasks,…

Computer Vision and Pattern Recognition · Computer Science 2017-02-22 Evgeny Levinkov , Jonas Uhrig , Siyu Tang , Mohamed Omran , Eldar Insafutdinov , Alexander Kirillov , Carsten Rother , Thomas Brox , Bernt Schiele , Bjoern Andres

We present time-efficient distributed algorithms for decomposing graphs with large edge or vertex connectivity into multiple spanning or dominating trees, respectively. As their primary applications, these decompositions allow us to achieve…

Data Structures and Algorithms · Computer Science 2013-11-22 Keren Censor-Hillel , Mohsen Ghaffari , Fabian Kuhn
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