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Few/Zero-shot learning is a big challenge of many classifications tasks, where a classifier is required to recognise instances of classes that have very few or even no training samples.
Generalized zero-shot ICD coding
Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, and Eric Xing. 2019 · 1909
Earlier work this paper cites.
Cold start thread recommendation as extreme multi-label classification
Kishaloy Halder, Lahari Poddar, and Min-Yen Kan. 2018 · 1918
Earlier work this paper cites.
Bayesian multi-label learning with sparse features and labels, and label co-occurrences
He Zhao, Piyush Rai, Lan Du, and Wray Buntine. 2018 · 1951
Earlier work this paper cites.
Medical coding classification by leveraging inter-code relationships
Yan Yan, Glenn Fung, Jennifer G. Dy, and Romer Rosales. 2010 · 2010
Earlier work this paper cites.
Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
Earlier work this paper cites.
Diagnosis code assignment: models and evaluation metrics
Adler Perotte, Rimma Pivovarov, Karthik Natarajan, Nicole Weiskopf, Frank Wood, and Noémie Elhadad. 2014 · 2014
Earlier work this paper cites.
An empirical evaluation of supervised learning approaches in assigning diagnosis codes to electronic medical records
Ramakanth Kavuluru, Anthony Rios, and Yuan Lu. 2015 · 2015
Earlier work this paper cites.
Recurrent convolutional neural networks for text classification
Siwei Lai, Liheng Xu, Kang Liu, and Jun Zhao. 2015 · 2015
Earlier work this paper cites.
The extreme classification repository: Multi-label datasets and code
K. Bhatia, K. Dahiya, H. Jain, A. Mittal, Y. Prabhu, and M. Varma. 2016 · 2016
Earlier work this paper cites.
MIMIC-III, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, H Lehman Li-wei, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark. 2016 · 2016
Earlier work this paper cites.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra. 2016 · 2016
Earlier work this paper cites.
Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
Earlier work this paper cites.
Graph convolutional networks for classification with a structured label space
Meihao Chen, Zhuoru Lin, and Kyunghyun Cho. 2017 · 2017
Earlier work this paper cites.
A probabilistic framework for zero-shot multi-label learning
Abhilash Gaure and Piyush Rai. 2017 · 2017
Earlier work this paper cites.
Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling. 2017 · 2017
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Deep learning for extreme multi-label text classification
Jingzhou Liu, Wei-Cheng Chang, Yuexin Wu, and Yiming Yang. 2017 · 2017
Cited alongside, same era.
Efficient large-scale multi-modal classification
Douwe Kiela, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2018 · 2018
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Multi-label zero-shot learning with structured knowledge graphs
Chung-Wei Lee, Wei Fang, Chih-Kuan Yeh, and Yu-Chiang Frank Wang. 2018 · 2018
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Explainable prediction of medical codes from clinical text
James Mullenbach, Sarah Wiegreffe, Jon Duke, Jimeng Sun, and Jacob Eisenstein. 2018 · 2018
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Few-shot and zero-shot multi-label learning for structured label spaces
Anthony Rios and Ramakanth Kavuluru. 2018 · 2018
Rethinking knowledge graph propagation for zero-shot learning
Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, and Eric P. Xing. 2019 · 2019
Later among the works it cites.
Multi-GCN: Graph convolutional networks for multi-view networks, with applications to global poverty
Muhammad Raza Khan and Joshua E Blumenstock. 2019 · 2019
Later among the works it cites.
NeuralClassifier: An open-source neural hierarchical multi-label text classification toolkit
Liqun Liu, Funan Mu, Pengyu Li, Xin Mu, Jing Tang, Xingsheng Ai, Ran Fu, Lifeng Wang, and Xing Zhou. 2019 · 2019
Later among the works it cites.
Multi-dimensional graph convolutional networks
Yao Ma, Suhang Wang, Chara C Aggarwal, Dawei Yin, and Jiliang Tang. 2019 · 2019
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Multi-label categorization of accounts of sexism using a neural framework
Pulkit Parikh, Harika Abburi, Pinkesh Badjatiya, Radhika Krishnan, Niyati Chhaya, Manish Gupta, and Vasudeva Varma. 2019 · 2019
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Zero-shot recognition via semantic embeddings and knowledge graphs
Xiaolong Wang, Yufei Ye, and Abhinav Gupta. 2018 · 2018
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Large-scale multi-label text classification on EU legislation
Ilias Chalkidis, Emmanouil Fergadiotis, Prodromos Malakasiotis, and Ion Androutsopoulos. 2019 · 2019
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Biosentvec: creating sentence embeddings for biomedical texts
Q. Chen, Y. Peng, and Z. Lu. 2019 · 2019
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Multi-label image recognition with graph convolutional networks
Zhao-Min Chen, Xiu-Shen Wei, Peng Wang, and Yanwen Guo. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Attentional multilabel learning over graphs: a message passing approach
Kien Do, Truyen Tran, Thin Nguyen, and Svetha Venkatesh. 2019 · 2019
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A survey of zero-shot learning: Settings, methods, and applications
Wei Wang, Vincent W. Zheng, Han Yu, and Chunyan Miao. 2019 · 2019
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Long-short distance aggregation networks for positive unlabeled graph learning
Man Wu, Shirui Pan, Lan Du, Ivor Tsang, Xingquan Zhu, and Bo Du. 2019 · 2019
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Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly
Yongqin Xian, Christoph H Lampert, Bernt Schiele, and Zeynep Akata. 2019 · 2019
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Label-specific document representation for multi-label text classification
Lin Xiao, Xin Huang, Boli Chen, and Liping Jing. 2019 · 2019
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Ehr coding with multi-scale feature attention and structured knowledge graph propagation
Xiancheng Xie, Yun Xiong, Philip S. Yu, and Yangyong Zhu. 2019 · 2019
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BioWordVec, improving biomedical word embeddings with subword information and mesh
Yijia Zhang, Qingyu Chen, Zhihao Yang, Hongfei Lin, and Zhiyong Lu. 2019 · 2019
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ICD coding from clinical text using multi-filter residual convolutional neural network
Fei Li and Hong Yu. 2020 · 2020
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Multi-label classification with label graph superimposing
Ya Wang, Dongliang He, Fu Li, Xiang Long, Zhichao Zhou, Jinwen Ma, and Shilei Wen. 2020 · 2020
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Cross-modality attention with semantic graph embedding for multi-label classification
Renchun You, Zhiyao Guo, Lei Cui, Xiang Long, Yingze Bao, and Shilei Wen. 2020 · 2020
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