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Graph neural networks have achieved state-of-the-art accuracy for graph node classification. However, GNNs are difficult to scale to large graphs, for example frequently encountering out-of-memory errors on even moderate size graphs. Recent…

Machine Learning · Computer Science 2022-10-26 Ziyuan Wang , Feiming Yang , Rui Fan

In this paper we present linear time approximation schemes for several generalized matching problems on nonbipartite graphs. Our results include $O_\epsilon(m)$-time algorithms for $(1-\epsilon)$-maximum weight $f$-factor and…

Data Structures and Algorithms · Computer Science 2020-05-11 Dawei Huang , Seth Pettie

Graph partition is a key component to achieve workload balance and reduce job completion time in parallel graph processing systems. Among the various partition strategies, edge partition has demonstrated more promising performance in…

Data Structures and Algorithms · Computer Science 2020-12-18 Zhenyu Guo , Mingyu Xiao , Yi Zhou , Dongxiang Zhang , Kian-Lee Tan

We study dynamic graph algorithms in the Massively Parallel Computation model, which was inspired by practical data processing systems. Our goal is to provide algorithms that can efficiently handle large batches of edge insertions and…

Data Structures and Algorithms · Computer Science 2021-01-12 Krzysztof Nowicki , Krzysztof Onak

In this work, we propose a novel approach for subgraph matching, the problem of finding a given query graph in a large source graph, based on the fused Gromov-Wasserstein distance. We formulate the subgraph matching problem as a partial…

Information Theory · Computer Science 2024-07-01 Wen-Xin Pan , Isabel Haasler , Pascal Frossard

We resolve the space complexity of linear sketches for approximating the maximum matching problem in dynamic graph streams where the stream may include both edge insertion and deletion. Specifically, we show that for any $\epsilon > 0$,…

Data Structures and Algorithms · Computer Science 2015-05-07 Sepehr Assadi , Sanjeev Khanna , Yang Li , Grigory Yaroslavtsev

Graph matching is one of the most significant graph analytic tasks, which aims to find the node correspondence across different graphs. Most existing graph matching approaches mainly rely on topological information, whose performances are…

Artificial Intelligence · Computer Science 2024-10-15 Haoran Cheng , Dixin Luo , Hongteng Xu

Finding a maximum-cardinality or maximum-weight matching in (edge-weighted) undirected graphs is among the most prominent problems of algorithmic graph theory. For $n$-vertex and $m$-edge graphs, the best known algorithms run in…

Data Structures and Algorithms · Computer Science 2021-05-10 Tomohiro Koana , Viatcheslav Korenwein , André Nichterlein , Rolf Niedermeier , Philipp Zschoche

We study dynamic $(1-\epsilon)$-approximate rounding of fractional matchings -- a key ingredient in numerous breakthroughs in the dynamic graph algorithms literature. Our first contribution is a surprisingly simple deterministic rounding…

Data Structures and Algorithms · Computer Science 2024-02-26 Sayan Bhattacharya , Peter Kiss , Aaron Sidford , David Wajc

We provide an algorithm that maintains, against an adaptive adversary, a $(1-\varepsilon)$-approximate maximum matching in $n$-node $m$-edge general (not necessarily bipartite) undirected graph undergoing edge deletions with high…

Data Structures and Algorithms · Computer Science 2024-12-05 Jiale Chen , Aaron Sidford , Ta-Wei Tu

A hypergraph spectral sparsifier of a hypergraph $G$ is a weighted subgraph $H$ that approximates the Laplacian of $G$ to a specified precision. Recent work has shown that similar to ordinary graphs, there exist $\widetilde{O}(n)$-size…

Data Structures and Algorithms · Computer Science 2025-02-07 Sanjeev Khanna , Huan Li , Aaron Putterman

We present parameterized streaming algorithms for the graph matching problem in both the dynamic and the insert-only models. For the dynamic streaming model, we present a one-pass algorithm that, with high probability, computes a…

Data Structures and Algorithms · Computer Science 2021-02-26 Jianer Chen , Qin Huang , Iyad Kanj , Ge Xia

In this paper we further investigate the well-studied problem of finding a perfect matching in a regular bipartite graph. The first non-trivial algorithm, with running time $O(mn)$, dates back to K\"{o}nig's work in 1916 (here $m=nd$ is the…

Data Structures and Algorithms · Computer Science 2008-11-18 Ashish Goel , Michael Kapralov , Sanjeev Khanna

In multistage perfect matching problems we are given a sequence of graphs on the same vertex set and asked to find a sequence of perfect matchings, corresponding to the sequence of graphs, such that consecutive matchings are as similar as…

Data Structures and Algorithms · Computer Science 2021-05-11 Markus Chimani , Niklas Troost , Tilo Wiedera

Our work presents a new iterative scheme to approximate the fixed points of nonexpansive mapping. The proposed algorithm is constructed to enhance convergence efficiency while preserving theoretical robustness. Under appropriate assumptions…

Functional Analysis · Mathematics 2026-01-12 Nida Izhar Mallick , Izhar Uddin

One of the biggest huddles faced by researchers studying algorithms for massive graphs is the lack of large input graphs that are essential for the development and test of the graph algorithms. This paper proposes two efficient and highly…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-03-22 Andy Yoo , Keith Henderson

In an undirected graph $G=(V,E)$, we say $(A,B)$ is a pair of perfectly matched sets if $A$ and $B$ are disjoint subsets of $V$ and every vertex in $A$ (resp. $B$) has exactly one neighbor in $B$ (resp. $A$). The size of a pair of perfectly…

Discrete Mathematics · Computer Science 2022-11-08 N. R. Aravind , Roopam Saxena

A matching in a graph is induced if no two of its edges are joined by an edge, and finding a large induced matching is a very hard problem. Lin et al. (Approximating weighted induced matchings, Discrete Applied Mathematics 243 (2018)…

Combinatorics · Mathematics 2018-12-17 Julien Baste , Maximilian Fürst , Dieter Rautenbach

Graph partitioning is a key fundamental problem in the area of big graph computation. Previous works do not consider the practical requirements when optimizing the big data analysis in real applications. In this paper, motivated by…

Databases · Computer Science 2024-04-10 Baoling Ning , Jianzhong Li

Graph matching pairs corresponding nodes across two or more graphs. The problem is difficult as it is hard to capture the structural similarity across graphs, especially on large graphs. We propose to incorporate high-order information for…

Artificial Intelligence · Computer Science 2020-10-12 Hui Xu , Liyao Xiang , Youmin Le , Xiaoying Gan , Yuting Jia , Luoyi Fu , Xinbing Wang