Spectrally approximating large graphs with smaller graphs

21 February 2018

Papers citing "Spectrally approximating large graphs with smaller graphs"

50 / 54 papers shown

Title
Taxonomy of reduction matrices for Graph Coarsening Antonin Joly Nicolas Keriven Aline Roumy 12 0 0 13 Jun 2025
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening Guoming Li Jian Yang Yifan Chen 207 0 0 20 May 2025
Graph Condensation: A Survey Xin Gao Junliang Yu Wei Jiang Tong Chen Wentao Zhang Hongzhi Yin DD 294 21 0 28 Jan 2025
Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training Shuyin Xia Xinjun Ma Zhiyuan Liu Cheng Liu Sen Zhao G. Wang 112 2 0 18 Dec 2024
PASCO (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms Etienne Lasalle Rémi Vaudaine Titouan Vayer Pierre Borgnat Rémi Gribonval Paulo Gonçalves Màrton Karsai 78 0 0 18 Dec 2024
SHyPar: A Spectral Coarsening Approach to Hypergraph Partitioning Hamed Sajadinia Ali Aghdaei Zhuo Feng 73 0 0 09 Oct 2024
Modularity aided consistent attributed graph clustering via coarsening Samarth Bhatia Yukti Makhija Manoj Kumar Sandeep Kumar 143 0 0 09 Jul 2024
On the Robustness of Graph Reduction Against GNN Backdoor Yuxuan Zhu Michael Mandulak Kerui Wu George Slota Yuseok Jeon Ka-Ho Chow Lei Yu AAML 60 1 0 02 Jul 2024
Efficient User Sequence Learning for Online Services via Compressed Graph Neural Networks Yucheng Wu Liyue Chen Yu Cheng Shuai Chen Jinyu Xu Leye Wang GNN 108 0 0 05 Jun 2024
Graph Coarsening with Message-Passing Guarantees Antonin Joly Nicolas Keriven 66 2 0 28 May 2024
Calibrated Dataset Condensation for Faster Hyperparameter Search Mucong Ding Yuancheng Xu Tahseen Rabbani Xiaoyu Liu Brian J Gravelle Teresa M. Ranadive Tai-Ching Tuan Furong Huang DD 72 0 0 27 May 2024
Spectral Greedy Coresets for Graph Neural Networks Mucong Ding Yinhan He Jundong Li Furong Huang 89 3 0 27 May 2024
Graph Condensation for Open-World Graph Learning Xin Gao Tong Chen Wentao Zhang Yayong Li Xiangguo Sun Hongzhi Yin 120 8 0 27 May 2024
Accelerating Transformers with Spectrum-Preserving Token Merging Hoai-Chau Tran D. M. Nguyen Duy M. Nguyen Trung Thanh Nguyen Ngan Le Pengtao Xie Daniel Sonntag James Y. Zou Binh T. Nguyen Mathias Niepert 106 13 0 25 May 2024
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition Xin Gao Tong Chen Wentao Zhang Junliang Yu Guanhua Ye Quoc Viet Hung Nguyen 137 8 0 22 May 2024
Simple Graph Condensation Zhenbang Xiao Yu Wang Shunyu Liu Huiqiong Wang Mingli Song Tongya Zheng DD 145 8 0 22 Mar 2024
TEDDY: Trimming Edges with Degree-based Discrimination strategY Hyunjin Seo Jihun Yun Eunho Yang 77 1 0 02 Feb 2024
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation Mohammad Hashemi Shengbo Gong Juntong Ni Wenqi Fan B. A. Prakash Wei Jin DD 145 51 0 29 Jan 2024
Disentangled Condensation for Large-scale Graphs Zhenbang Xiao Shunyu Liu Yu Wang Tongya Zheng Mingli Song Mingli Song Tongya Zheng DD 255 7 0 18 Jan 2024
Efficient and Scalable Graph Generation through Iterative Local Expansion Andreas Bergmeister Karolis Martinkus Nathanael Perraudin Roger Wattenhofer 83 16 0 14 Dec 2023
Does Graph Distillation See Like Vision Dataset Counterpart? Beining Yang Kai Wang Qingyun Sun Cheng Ji Xingcheng Fu Hao Tang Yang You Jianxin Li DD 71 45 0 13 Oct 2023
Data-centric Graph Learning: A Survey Jixi Liu Deyu Bo Cheng Yang Haoran Dai Qi Zhang Yixin Xiao Yufei Peng Chuan Shi GNN 92 21 0 08 Oct 2023
Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery Ticket Yuwen Wang Shunyu Liu Kai Chen Tongtian Zhu Jilin Qiao Mengjie Shi Yuanyu Wan Mingli Song 61 6 0 05 Aug 2023
Graph Condensation for Inductive Node Representation Learning Xin Gao Tong Chen Yilong Zang Wentao Zhang Quoc Viet Hung Nguyen Kai Zheng Hongzhi Yin DD AI4CE 105 38 0 29 Jul 2023
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware Shichang Zhang Atefeh Sohrabizadeh Cheng Wan Zijie Huang Ziniu Hu Yewen Wang Yingyan Lin Lin Jason Cong Yizhou Sun GNN AI4CE 96 25 0 24 Jun 2023
A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening Yifan Chen Rentian Yao Yun Yang Jie Chen 86 8 0 15 Jun 2023
Graph Filters for Signal Processing and Machine Learning on Graphs Elvin Isufi Fernando Gama D. Shuman Santiago Segarra GNN 88 72 0 16 Nov 2022
HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering Ali Aghdaei Zhuo Feng 47 9 0 26 Oct 2022
A Unified Framework for Optimization-Based Graph Coarsening Manoj Kumar Anurag Sharma Surinder Kumar 44 16 0 02 Oct 2022
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks Chuang Liu Xueqi Ma Yinbing Zhan Liang Ding Dapeng Tao Di Lin Wenbin Hu Danilo Mandic 72 32 0 18 Jul 2022
FunQG: Molecular Representation Learning Via Quotient Graphs H. Hajiabolhassan Zahra Taheri Ali Hojatnia Yavar Taheri Yeganeh 29 8 0 18 Jul 2022
SMGRL: Scalable Multi-resolution Graph Representation Learning Reza Namazi Elahe Ghalebi Sinead Williamson H. Mahyar 70 1 0 29 Jan 2022
SQALER: Scaling Question Answering by Decoupling Multi-Hop and Logical Reasoning Mattia Atzeni Jasmina Bogojeska Andreas Loukas ReLM LRM 73 15 0 27 Oct 2021
Graph Condensation for Graph Neural Networks Wei Jin Lingxiao Zhao Shichang Zhang Yozen Liu Jiliang Tang Neil Shah DD AI4CE 148 162 0 14 Oct 2021
HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering Ali Aghdaei Zhiqiang Zhao Zhuo Feng 36 8 0 17 Aug 2021
Partition and Code: learning how to compress graphs Giorgos Bouritsas Andreas Loukas Nikolaos Karalias M. Bronstein 77 13 0 05 Jul 2021
Interferometric Graph Transform for Community Labeling Nathan Grinsztajn Louis Leconte Philippe Preux Edouard Oyallon 46 1 0 04 Jun 2021
Low-Rank Projections of GCNs Laplacian Nathan Grinsztajn Philippe Preux Edouard Oyallon 21 1 0 04 Jun 2021
Graph Coarsening with Neural Networks Chen Cai Dingkang Wang Yusu Wang DD 182 68 0 02 Feb 2021
Chordal Decomposition for Spectral Coarsening Honglin Chen Hsueh-Ti Derek Liu Alec Jacobson David I. W. Levin 42 12 0 04 Sep 2020
SF-GRASS: Solver-Free Graph Spectral Sparsification Ying Zhang Zhiqiang Zhao Zhuo Feng 38 12 0 17 Aug 2020
Faster Graph Embeddings via Coarsening Matthew Fahrbach Gramoz Goranci Richard Peng Sushant Sachdeva Chi Wang 65 28 0 06 Jul 2020
Gaussian Processes on Graphs via Spectral Kernel Learning Yin-Cong Zhi Yin Cheng Ng Xiaowen Dong 53 32 0 12 Jun 2020
COPT: Coordinated Optimal Transport for Graph Sketching Yihe Dong W. Sawin OT 104 26 0 09 Mar 2020
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport Tengfei Ma Jie Chen 71 25 0 24 Dec 2019
GRASPEL: Graph Spectral Learning at Scale Yongyu Wang Zhiqiang Zhao Zhuo Feng 396 4 0 23 Nov 2019
Human Action Recognition with Multi-Laplacian Graph Convolutional Networks A. Mazari H. Sahbi GNN 41 5 0 15 Oct 2019
Structured Graph Learning Via Laplacian Spectral Constraints Sandeep Kumar Jiaxi Ying J. Cardoso Daniel P. Palomar 115 58 0 24 Sep 2019
A graphical heuristic for reduction and partitioning of large datasets for scalable supervised training Sumedh Yadav Mathis Bode 36 3 0 24 Jul 2019
Solving graph compression via optimal transport Vikas Garg Tommi Jaakkola OT 67 16 0 29 May 2019