This is a list of some important multi-label learning that serious students and researches working in the field should probably know about and read.
This list is far from complete or objective, and is evolving, as important papers are being published year after year. Please let me know via pull requests and issues if anything is missing.
Also, I did not try to include links to original papers since there is a lot of work to keep dead links up to date. I'm sure most of the papers listed here via a single Google search by their titles.
A paper does not have to be a peer-reviewed conference/journal paper to appear here. We also include tutial/survey-style papers and blog posts that often eaiser to understand than the original papers.
Minling Zhang: A Review on Multi-Label Learning Algorithms, in KDD 2013.
Minling Zhang: ML-KNN: A Lazy Learning Approach to Multi-Label Learning, in Pattern Recognition 2007.
Johannes Fürnkranz: Multilabel Classification via Calibrated Label Ranking, in Machine Learning 2008.
Zhihua Zhou: Multi-instance Multi-label Learning, in Artificial Intelligence 2008.
Yuxiong Wang: Learning to Model the Tail, in NIPS 2017.
Rohit Babbar: Adversarial Extreme Multi-label Classification, in arXiv 2018.
Xuan Wu: Multi-View Multi-Label Learning with View-Specific Information Extraction, in IJCAI 19.
Fernando Benites: HARAM: A Hierarchical ARAM Neural Network for Large-scale Text Classification, IEEE International Conference on Data Mining Workshops 2015.
Jianqing Zhu: Multi-label Convolutional Neural Network based Pedestrian Attribute Classification, In Image & Vision Computing 2017.
Wenjie Zhang: Deep Extreme Multi-label Learning, arXiv preprint arXiv:1704.03718. 2017 Apr 12.
CK Yeh: Learning Deep Latent Spaces for Multi-Label Classification, in AAAI 2017.
Sameera Ramasinghe: A Context-aware Capsule Network for Multi-label Classification, in arXiv 2018.
Rami Aly: Hierarchical Multi-label Classification of Text with Capsule Networks, in ACL 2019.
Pengcheng Yang: SGM: Sequence Generation Model for Multi-Label Classification, in COLING 2018.
Pengcheng Yang: A Deep Reinforced Sequence-to-Set Model for Multi-Label Text Classification, in ACL 2019.
Siddhartha Banerjee: Hierarchical Transfer Learning for Multi-label Text Classification, in ACL 2019.
Yongcheng Liu: Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection, in ACM Multimedia(MM) 2018.
Shiyi He: Reinforced Multi-Label Image Classification by Exploring Curriculum, in AAAI 2018.
Jiang Wang: CNN-RNN: A Unified Framework for Multi-label Image Classification, in CVPR 2016.
Yunchao Wei: HCP: A Flexible CNN Framework for Multi-Label Image Classification, in TPAMI 2016.
Tianshui Chen: Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition, in AAAI 2018.
Thibaut Durand: Learning a Deep ConvNet for Multi-label Classification with Partial Labels, in CVPR 2019.
Zhaomin chen: Multi-Label Image Recognition with Graph Convolutional Networks, in CVPR 2019.
JônatasWehrmann: Hierarchical Multi-Label Classification Networks, in ICML 2018.
Samy Bengio: Label Embedding Trees for Large Multi-Class Tasks, in NIPS 2010.
Jia Deng: Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition, in NIPS 2011.
Wei Bi: Multi-Label Classification on Tree-and DAG Structured, in ICML 2011.
Piotr Szyma´nski: LNEMLC: Label Network Embeddings for Multi-Label Classifiation, in Arxiv 2018.
Xin Li: Multi-Label Classification with Feature-Aware Non-Linear Label Space Transformation, in IJCAI 2015.
Keigo Kimura: Simultaneous Nonlinear Label-Instance Embedding for Multi-label Classification, in Joint IAPR 2016.
Cheng Gong: Teaching-to-Learning-to-Teach for Multi-Label Propagation, in AAAI 2016.
Kang Zhao: Top-N Recommender System via Matrix Completion, in AAAI 2016
Joonseok Lee: Local Collaborative Ranking, in WWW pp 85-96 ACM 2014.
Steven C. H. Hoi: Online Learning: A Comprehensive Survey, in CoRR 2018.
Young hun Jung: Online Boosting Algorithms for Multi-label Ranking, in arXiv 2017.
Hongming Chu: Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification, in CoRR 2017.
Alican Büyükçakır: A Novel Online Stacked Ensemble for Multi-Label Stream Classification, in ACM CIKM 2018.
Sophie Burkhardt1: Online multi-label dependency topic models for text classification, in Machine Learning vol 107 pp 859-886 2018.
Zahra Ahmadi: Online Multi-Label Classification: A Label Compression Method, in Pattern Recognition Letters(PRL) 2018.
Aljaž Osojnik: Multi-label Classification via Multi-target Regression on Data Streams, in Machine Learning vol 2016 pp 745-770 2017.
Shan You: Privileged Multi-Label Learning, in IJCAI 2017.
Shenjun Huang: Multi-Label Hypothesis Reuse, in KDD (Best Paper) 2012.
Mingkun Xie: Partial Multi-Label Learning, in AAAI 2018.
Qianwen Zhang: Feature-Induced Labeling Information Enrichment for Multi-Label Learning, in AAAI 2018.
Lei Feng: Collaboration based Multi-Label Learning, in AAAI 2019.
Wu Jiawei: Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification, in EMNLP 2019.