罗氏和博阿齐奇大学研究合作团队提出:多标签文本分类中长尾分布的平衡策略|EMNLP 2021 | 损失函数( 四 )



Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, and Daniel Weld. 2020. SPECTER: Document-level representation learning using citation-informed transformers. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2270–2282, Online. Association for Computational Linguistics.

NCBI Resource Coordinators. 2017. Database resources of the National Center for Biotechnology Information. Nucleic Acids Research, 46(D1):D8–D13.

Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, and Serge Belongie. 2019. Class-balanced loss based on effective number of samples. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9260–9269.

Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.

T. Durand, N. Mehrasa, and G. Mori. 2019. Learning a deep convnet for multi-label classification with partial labels. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 647–657, Los Alamitos, CA, USA. IEEE Computer Society.

Andrew Estabrooks, Taeho Jo, and Nathalie Japkowicz. 2004. A multiple resampling method for learning from imbalanced data sets. Computational intelligence, 20(1):18–36.

Weifeng Ge, Sibei Yang, and Yizhou Yu. 2018. Multievidence filtering and fusion for multi-label classification, object detection and semantic segmentation based on weakly supervised learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Philip J. Hayes and Steven P. Weinstein. 1990. Construe/tis: A system for content-based indexing of a database of news stories. In Proceedings of the The Second Conference on Innovative Applications of Artificial Intelligence, IAAI ’90, page 49–64. AAAI Press.

Gakuto Kurata, Bing Xiang, and Bowen Zhou. 2016. Improved neural network-based multi-label classification with better initialization leveraging label cooccurrence. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 521–526.

Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2019. BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics.

Jianqiang Li, Guanghui Fu, Yueda Chen, Pengzhi Li, Bo Liu, Yan Pei, and Hui Feng. 2020a. A multilabel classification model for full slice brain computerised tomography image. BMC Bioinformatics, 21(6):200.

Xiaoya Li, Xiaofei Sun, Yuxian Meng, Junjun Liang, Fei Wu, and Jiwei Li. 2020b. Dice loss for dataimbalanced NLP tasks. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 465–476, Online. Association for Computational Linguistics.

Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár. 2017. Focal loss for dense object detection. In 2017 IEEE International Conference on Computer Vision (ICCV), pages 2999–3007, Los Alamitos, CA, USA. IEEE Computer Society.

Zachary C. Lipton, Charles Elkan, and Balakrishnan Naryanaswamy. 2014. Optimal thresholding of classifiers to maximize f1 measure. In Machine Learning and Knowledge Discovery in Databases, pages 225–239, Berlin, Heidelberg. Springer Berlin Heidelberg. Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi. 2016. V-net: Fully convolutional neural networks for volumetric medical image segmentation. In 2016 Fourth International Conference on 3D Vision (3DV), pages 565–571.

Jinseok Nam, Eneldo Loza Mencía, Hyunwoo J Kim, and Johannes Fürnkranz. 2017. Maximizing subset accuracy with recurrent neural networks in multilabel classification. In Advances in Neural Information Processing Systems, volume 30. Curran Associates, Inc.

Ankit Pal, Muru Selvakumar, and Malaikannan Sankarasubbu. 2020. Magnet: Multi-label text classification using attention-based graph neural network. In ICAART (2), pages 494–505.