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Text classification is a critical research topic with broad applications in natural language processing.
Feature interaction-aware graph neural networks
Kaize Ding, Yichuan Li, Jundong Li, Chenghao Liu, and Huan Liu. 2019b · 1908
Earlier work this paper cites.
Latent dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan. 2003 · 2003
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Graph prototypical networks for few-shot learning on attributed networks
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
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Baselines and bigrams: Simple, good sentiment and topic classification
Sida Wang and Christopher D Manning. 2012 · 2012
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Adam: A method for stochastic optimization
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Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D Manning. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016 · 2016
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Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2016 · 2016
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Recurrent neural network for text classification with multi-task learning
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Deep patient: an unsupervised representation to predict the future of patients from the electronic health records
Riccardo Miotto, Li Li, Brian A Kidd, and Joel T Dudley. 2016 · 2016
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Attention-based lstm for aspect-level sentiment classification
Yequan Wang, Minlie Huang, Xiaoyan Zhu, and Li Zhao. 2016 · 2016
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Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
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Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms
Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, and Lawrence Carin. 2018 · 2018
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Joint embedding of words and labels for text classification
Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, and Lawrence Carin. 2018 · 2018
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Graph neural networks: A review of methods and applications
Jie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, and Maosong Sun. 2018 · 2018
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Hypergraph neural networks
Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji, and Yue Gao. 2019 · 2019
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Text level graph neural network for text classification
Lianzhe Huang, Dehong Ma, Sujian Li, Xiaodong Zhang, and Houfeng WANG. 2019 · 2019
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl. 2017 · 2017
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Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017 · 2017
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Semi-supervised classification with graph convolutional networks
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Relational inductive biases, deep learning, and graph networks
Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, et al. 2018 · 2018
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Deep anomaly detection on attributed networks
Kaize Ding, Jundong Li, Rohit Bhanushali, and Huan Liu. 2019a
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Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 201b
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Heterogeneous graph attention networks for semi-supervised short text classification
Hu Linmei, Tianchi Yang, Chuan Shi, Houye Ji, and Xiaoli Li. 2019 · 2019
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Graph convolutional networks for text classification
Liang Yao, Chengsheng Mao, and Yuan Luo. 2019 · 2019
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Hypergraph convolution and hypergraph attention
Song Bai, Feihu Zhang, and Philip HS Torr. 2020 · 2020
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Tensor graph convolutional networks for text classification
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Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, and James Caverlee. 2020 · 2020
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