Collective Classification in Network Data

Cited by (1,004)

Items 301–400 of 1,004

1. Exploring Structure-Adaptive Graph Learning for Robust Semi-Supervised Classification
   Xiang Gao, Wei Hu, Zongming Guo · 2020 · IEEE International Conference on Multimedia and Expo (ICME)
2. Batch virtual adversarial training for graph convolutional networks
   Zhijie Deng, Yinpeng Dong, Jun Zhu · 2023 · AI Open
3. WSNMF: Weighted Symmetric Nonnegative Matrix Factorization for attributed graph clustering
   Kamal Berahmand, Mehrnoush Mohammadi, Razieh Sheikhpour, Yuefeng Li, Yue Xu · 2023 · Neurocomputing
4. Adaptive community detection incorporating topology and content in social networks✰
   Meng Qin, Di Jin, Kai Lei, Bogdan Gabryś, Katarzyna Musial-Gabrys · 2018 · Knowledge-Based Systems
5. End to end learning and optimization on graphs
   Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe · 2019 · arXiv (Cornell University)
6. Cautious Collective Classification
   Luke K. McDowell, Kalyan Moy Gupta, David W. Aha · 2009
7. Superpixel Image Classification with Graph Attention Networks
   Pedro Avelar, Anderson Rocha Tavares, Thiago L. T. da Silveira, Cláudio R. Jung, Luís C. Lamb · 2020 · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
8. Inductive Link Prediction for Nodes Having Only Attribute Information
   Yu Hao, Xin Cao, Yixiang Fang, Xike Xie, Sibo Wang · 2020 · International Joint Conference on Artificial Intelligence
9. A new attributed graph clustering by using label propagation in complex networks
   Kamal Berahmand, Sogol Haghani, Mehrdad Rostami, Yuefeng Li · 2020 · Journal of King Saud University - Computer and Information Sciences
10. Causal GraphSAGE: A robust graph method for classification based on causal sampling
    Tao Zhang, Haoran Shan, Max A. Little · 2022 · Pattern Recognition
11. Adaptively Connected Neural Networks
    Guangrun Wang, Keze Wang, Liang Lin · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
12. Incorporating network structure with node contents for community detection on large networks using deep learning
    Jinxin Cao, Di Jin, Liang Yang, Jianwu Dang · 2018 · Neurocomputing
13. Scalable Graph Neural Networks via Bidirectional Propagation
    Chen, Ming, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, Ji-Rong Wen · 2020 · arXiv (Cornell University)
14. Leveraging high-level and low-level features for multimedia event detection
    Lu Jiang, Alexander G. Hauptmann, Guang Xiang · 2012 · ACM International Conference on Multimedia (ACM MM)
15. Transfer Learning across Networks for Collective Classification
    Meng Fang, Jie Yin, Xingquan Zhu A · 2013 · Proceedings
16. Exploiting Centrality Information with Graph Convolutions for Network Representation Learning
    Hongxu Chen, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wen-Chih Peng, Xue Li · 2019 · IEEE International Conference on Data Engineering (ICDE)
17. Graph Few-shot Learning with Attribute Matching
    Ning Wang, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, Qinghua Zheng · 2020 · ACM International Conference on Information and Knowledge Management (CIKM)
18. Dual Feature Interaction-Based Graph Convolutional Network
    Zhongying Zhao, Yang Zhan, Chao Li, Qingtian Zeng, Weili Guan, MengChu Zhou · 2022 · IEEE Transactions on Knowledge and Data Engineering
19. Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
    Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent C. S. Lee, Shirui Pan · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
20. Permutation Invariant Graph Generation via Score-Based Generative Modeling
    Chenhao Niu, Yang Sup Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon · 2020 · arXiv (Cornell University)
21. Bibliographic analysis on research publications using authors, categorical labels and the citation network
    Kar Wai Lim, Wray Buntine · 2016 · Machine Learning
22. Automated Machine Learning on Graphs: A Survey
    Ziwei Zhang, Xin Wang, Wenwu Zhu · 2021 · International Joint Conference on Artificial Intelligence
23. Block Modeling-Guided Graph Convolutional Neural Networks
    Dongxiao He, Chundong Liang, Huixin Liu, Mingxiang Wen, Pengfei Jiao, Zhiyong Feng · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
24. Disease prediction with edge-variational graph convolutional networks
    Yongxiang Huang, Albert C. S. Chung · 2022 · Medical Image Analysis
25. Imitation Learning-Based Implicit Semantic-Aware Communication Networks: Multi-Layer Representation and Collaborative Reasoning
    Yong Liang Xiao, Zijian Sun, Guangming Shi, Dusit Tao Niyato · 2022 · IEEE Journal on Selected Areas in Communications
26. Active Discriminative Network Representation Learning
    Li Fu Gao, Hong Tao Yang, Chuan De Zhou, Jia Xin Wu, Shirui Pan, Yue Hu · 2018 · International Joint Conference on Artificial Intelligence
27. Quantum-based subgraph convolutional neural networks
    Zhihong Zhang, Dongdong Chen, Jianjia Wang, Lu Bai, Edwin R. Hancock · 2018 · Pattern Recognition
28. Overlapping Community Detection in Directed and Undirected Attributed Networks Using a Multiobjective Evolutionary Algorithm
    Xiangyi Teng, Jing Liu, Mingming Li · 2019 · IEEE Transactions on Cybernetics
29. Understanding Structural Vulnerability in Graph Convolutional Networks
    Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, Carl Yang · 2021 · International Joint Conference on Artificial Intelligence
30. Anomaly, event, and fraud detection in large network datasets
    Leman Akoglu, Christos Faloutsos · 2013 · ACM International Conference on Web Search and Data Mining (WSDM)
31. GraphDF: A Discrete Flow Model for Molecular Graph Generation
    Youzhi Luo, Keqiang Yan, Shuiwang Ji · 2021 · arXiv (Cornell University)
32. A Variational Bayesian Framework for Cluster Analysis in a Complex Network
    Lun Hu, Keith C. C. Chan, Xiaohui Yuan, Shengwu Xiong · 2019 · IEEE Transactions on Knowledge and Data Engineering
33. Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology
    Mark Cheung, John Shi, Oren Wright, Lavendar Y. Jiang, Xujin Liu, José M. F. Moura · 2020 · IEEE Signal Processing Magazine
34. DropMessage: Unifying Random Dropping for Graph Neural Networks
    Taoran Fang, Zhiqing Xiao, Chunping Wang, Jiarong Xu, Xuan Yang, Yang Yang · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
35. Tree Decomposed Graph Neural Network
    Yu Wang, Tyler Derr · 2021 · ACM International Conference on Information and Knowledge Management (CIKM)
36. GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design
    Haoran You, Tong Geng, Yongan Zhang, Ang Li, Yingyan Lin · 2022 · IEEE International Symposium on High-Performance Computer Architecture (HPCA)
37. Modularity-aware graph autoencoders for joint community detection and link prediction
    Guillaume Salha-Galvan, Johannes F. Lutzeyer, George Dasoulas, Romain Hennequin, Michalis Vazirgiannis · 2022 · Neural Networks
38. Transforming Graph Data for Statistical Relational Learning
    Ryan A. Rossi, Luke K. McDowell, David W. Aha, Jennifer Neville · 2012 · Journal of Artificial Intelligence Research
39. Effective label acquisition for collective classification
    Mustafa Bilgic, Lise C. Getoor · 2008 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
40. CiteSeer x : A Scholarly Big Dataset
    Cornelia Caragea, Jian Feng Wu, Alina Maria Ciobanu, Kyle Williams, Juan Fernández-Ramírez, Hung‐Hsuan Chen, Zhaohui Wu, Clyde Lee Giles · 2014 · Lecture notes in computer science
41. HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs
    Devanshu Arya, Deepak Kumar Gupta, Stevan Rudinac, Marcel Worring · 2020 · arXiv (Cornell University)
42. Co-clustering of Multi-view Datasets: A Parallelizable Approach
    Gilles Bisson, Clément Grimal · 2012 · Proceedings
43. Optimizing Text Quantifiers for Multivariate Loss Functions
    Andrea Esuli, Fabrizio Sebastiani · 2015 · ACM Transactions on Knowledge Discovery from Data
44. Social Network Analysis with Content and Graphs
    William M. Campbell, Charlie K. Dagli, Clifford J. Weinstein · 2013
45. Network Embedding With Completely-Imbalanced Labels
    Zheng Wang, Xiaojun Ye, Chaokun Wang, Jian Cui, Philip S. Yu · 2020 · IEEE Transactions on Knowledge and Data Engineering
46. Graph Lifelong Learning: A Survey
    Falih Gozi Febrinanto, Feng Xia, Kristen Moore, Chandra Thapa, Charų C. Aggarwal · 2023 · IEEE Computational Intelligence Magazine
47. edge2vec: Representation learning using edge semantics for biomedical knowledge discovery
    Zheng Gao, Gang Fu, Chunping Ouyang, Satoshi Tsutsui, Xiaozhong Liu, Jeremy J. Yang, Christopher R. Gessner, Brian Foote, David J. Wild, Ying Ding et al. · 2019 · BMC Bioinformatics
48. Constant Curvature Graph Convolutional Networks
    Gregor Bachmann, Gary Bécigneul, Octavian-Eugen Ganea · 2019 · arXiv (Cornell University)
49. Collaborative Graph Convolutional Networks: Unsupervised Learning Meets Semi-Supervised Learning
    Binyuan Hui, Pengfei Zhu, Qinghua Hu · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
50. Graph Neural Network with curriculum learning for imbalanced node classification
    Xiaohe Li, Zide Fan, Feilong Huang, Xuming Hu, Yawen Deng, Lei Wang, Xinyu Zhao · 2024 · Neurocomputing
51. Molecular Function Prediction Using Neighborhood Features
    Petko Bogdanov, Ambuj K. Singh · 2009 · IEEE Transactions on Computational Biology and Bioinformatics
52. Multi-label relational neighbor classification using social context features
    Xi Wang, Gita Sukthankar · 2013 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
53. Towards More Practical Adversarial Attacks on Graph Neural Networks
    Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei · 2020 · arXiv (Cornell University)
54. Uncertainty Aware Semi-Supervised Learning on Graph Data
    Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho · 2020 · arXiv (Cornell University)
55. NeutronStar: Distributed GNN Training with Hybrid Dependency Management
    Qiange Wang, Yanfeng Zhang, Hao Wang, Chaoyi Chen, Xiaodong Zhang, Ge Yu · 2022 · ACM SIGMOD International Conference on Management of Data (SIGMOD)
56. Statistical models of music-listening sessions in social media
    Elena Zheleva, John Guiver, Eduarda Mendes Rodrigues, Nataša Milić-Frayling · 2010 · International World Wide Web Conference (WWW)
57. Graph convolutional networks: analysis, improvements and results
    Ihsan Ullah, Mario Manzo, Mitul Shah, Michael G. Madden · 2021 · Applied Intelligence
58. Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation
    Binghui Wang, Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong · 2021 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
59. Applications of graph convolutional networks in computer vision
    Pingping Cao, Zeqi Zhu, Ziyuan Wang, Yanping Zhu, Qiang Niu · 2022 · Neural Computing and Applications
60. Federated Graph Semantic and Structural Learning
    Wenke Huang, Guancheng Wan, Mang Ye, Bo Du · 2023 · International Joint Conference on Artificial Intelligence
61. When Do GNNs Work: Understanding and Improving Neighborhood Aggregation
    Yiqing Xie, Sha Li, Carl Yang, Raymond Chi-Wing Wong, Jiawei Han · 2020 · International Joint Conference on Artificial Intelligence
62. Local Augmentation for Graph Neural Networks
    Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu · 2021 · arXiv (Cornell University)
63. Hypergraph clustering by iteratively reweighted modularity maximization
    Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran · 2020 · Applied Network Science
64. GRLC: Graph Representation Learning With Constraints
    Liang Peng, Yujie Mo, Jie Xu, Jialie Shen, Xiaoshuang Shi, Xiaoxiao Li, Heng Tao Shen, Xiaofeng Zhu · 2023 · IEEE Transactions on Neural Networks and Learning Systems
65. Graph Representation Learning and Its Applications: A Survey
    Van Thuy Hoang, Hyeon-Ju Jeon, Eun-Soon You, Yoewon Yoon, Sungyeop Jung, O‐Joun Lee · 2023 · Sensors
66. GraphCL: Contrastive Self-Supervised Learning of Graph Representations
    Hakim Hafidi, Mounir Ghogho, Philippe Ciblat, Ananthram Swami · 2020 · arXiv (Cornell University)
67. HesGCN: Hessian graph convolutional networks for semi-supervised classification
    Sichao Fu, Weifeng Liu, Dapeng Tao, Yicong Zhou, Liqiang Nie · 2019 · Information Sciences
68. Model Inversion Attacks Against Graph Neural Networks
    Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee‐Kong Lee, Enhong Chen · 2022 · IEEE Transactions on Knowledge and Data Engineering
69. Integration of pre-trained protein language models into geometric deep learning networks
    Fang Wu, Lirong Wu, Dragomir Radev, Jinbo Xu, Stan Ziqing Li · 2023 · Communications Biology
70. ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection
    Junwei He, Qianqian Xu, Yangbangyan Jiang, Zitai Wang, Qingming Huang · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence
71. GraphMI: Extracting Private Graph Data from Graph Neural Networks
    Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, Enhong Chen · 2021 · International Joint Conference on Artificial Intelligence
72. Detecting Campaign Promoters on Twitter Using Markov Random Fields
    Huayi Li, Arjun Mukherjee, Bing Liu, Rachel Kornfield, Sherry Emery · 2014 · Proceedings
73. Monophily in social networks introduces similarity among friends-of-friends
    Kristen M. Altenburger, Johan H. Ugander · 2018 · Nature Human Behaviour
74. EmbeddingVis: A Visual Analytics Approach to Comparative Network Embedding Inspection
    Quan Li, Kristanto Sean Njotoprawiro, Hammad Haleem, Qiaoan Chen, Chris Yi, Xiaojuan Ma · 2018 · IEEE Conference on Visual Analytics Science and Technology (VAST)
75. Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study
    Brian J. Gallagher, Tina Eliassi‐Rad · 2010 · Lecture notes in computer science
76. AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
    Ke Sun, Zhanxing Zhu, Zhouchen Lin · 2019 · arXiv (Cornell University)
77. Principled approach to the selection of the embedding dimension of networks
    Weiwei Gu, Aditya Tandon, Yong‐Yeol Ahn, Filippo Radicchi · 2021 · Nature Communications
78. Knowledge Graphs for drug repurposing: a review of databases and methods
    Pablo Perdomo-Quinteiro, Alberto Belmonte-Hernández · 2024 · Briefings in Bioinformatics
79. Gryphon: a semi-supervised anomaly detection system based on one-class evolving spiking neural network
    Konstantinos Demertzis, Lazaros Iliadis, Ilias Bougoudis · 2019 · Neural Computing and Applications
80. Learning Conjoint Attentions for Graph Neural Nets
    Tiantian He, Yew-Soon Ong, Lu Bai · 2021 · arXiv (Cornell University)
81. Adaptive Unsupervised Feature Selection on Attributed Networks
    Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu · 2019 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
82. GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation
    Nikhil Goyal, Harsh Vardhan Jain, Sayan Ranu · 2020 · International World Wide Web Conference (WWW)
83. Toward Equivalent Transformation of User Preferences in Cross Domain Recommendation
    Xu Chen, Ya Zhang, Ivor Wai-Hung Tsang, Yuangang Pan, Jingchao Su · 2022 · ACM Transactions on Information Systems
84. Protein Function Prediction Based on PPI Networks: Network Reconstruction vs Edge Enrichment
    Jiaogen Zhou, Wei Xiong, Yang Wang, Jihong Guan · 2021 · Frontiers in Genetics
85. Preference-oriented Social Networks
    Amirali Salehi‐Abari, Craig E. Boutilier · 2015 · ACM Conference on Recommender Systems (RecSys)
86. On Embedding Uncertain Graphs
    Jiafeng Hu, Reynold C. K. Cheng, Zhipeng Huang, Yixang Fang, Siqiang Luo · 2017 · ACM International Conference on Information and Knowledge Management (CIKM)
87. Evaluation of Community Detection Methods
    Xin Liu, Huimin Cheng, Zhongyuan Zhang · 2019 · IEEE Transactions on Knowledge and Data Engineering
88. TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs
    Meng Fang, Jie Yin, Xingquan Zhu A, Chengqi Zhang · 2015 · IEEE Transactions on Knowledge and Data Engineering
89. Multi-Task Network Representation Learning
    Yu Xie, Peixuan Jin, Maoguo Gong, Chen Bo Calvin Zhang, Bin Yu · 2020 · Frontiers in Neuroscience
90. Seastar
    Yidi Wu, Kaihao Ma, Zhenkun Cai, Tatiana Jin, Boyang Li, Chenguang Zheng, James Sheung-Chak Cheng, Fan Yu · 2021 · European Conference on Computer Systems
91. MatchSim: a novel similarity measure based on maximum neighborhood matching
    Zhenjiang Lin, Michael Rung-Tsong Lyu, Irwin King · 2011 · Knowledge and Information Systems
92. Learning Community Structure with Variational Autoencoder
    Jun Jin Choong, Xin Liu, Tsuyoshi Murata · 2018 · Proceedings
93. Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study
    Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Jiliang Tang · 2020
94. Bi-GCN: Binary Graph Convolutional Network
    Junfu Wang, Yunhong Wang, Zhen Yang, Liang Yang, Yuanfang Guo · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
95. Bayesian Graph Local Extrema Convolution with Long-tail Strategy for Misinformation Detection
    Guixian Zhang, Shichao Zhang, Guan Yuan · 2024 · ACM Transactions on Knowledge Discovery from Data
96. Community Detection on Large Complex Attribute Network
    Zhe Chen, Aixin Sun, Xiaokui Xiao · 2019 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
97. Graph Representation Learning via Hard and Channel-Wise Attention Networks
    Hongyang Gao, Shuiwang Ji · 2019 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
98. Topology-Imbalance Learning for Semi-Supervised Node Classification
    Deli Chen, Yankai Lin, Guangxiang Zhao, Xuancheng Ren, Peng Li, Jie Zhou, Xu Sun · 2021 · arXiv (Cornell University)
99. Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning
    Jiwoong Park, Minsik Lee, Hyung Jin Chang, Kyuewang Lee, Jin Young Choi · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
100. Variational co-embedding learning for attributed network clustering
     Shuiqiao Yang, Sunny Verma, Borui Cai, Jiaojiao Jiang, Kun Yu, Chen Fang, Shui Yu · 2023 · Knowledge-Based Systems