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Information-theoretic semi-supervised metric learning via entropy regularization
Gang Niu, Bo Dai, Makoto Yamada, and Masashi Sugiyama · 2014
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Tongliang Liu and Dacheng Tao · 2015
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Learning from massive noisy labeled data for image classification
Tong Xiao, Tian Xia, Yi Yang, Chang Huang, and Xiaogang Wang · 2015
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Neural network-based clustering using pairwise constraints
Yen-Chang Hsu and Zsolt Kira · 2016
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The unreasonable effectiveness of noisy data for fine-grained recognition
Jonathan Krause, Benjamin Sapp, Andrew Howard, Howard Zhou, Alexander Toshev, Tom Duerig, James Philbin, and Li Fei-Fei · 2016
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Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals · 2016
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Learning with bounded instance-and label-dependent label noise
Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, and Dacheng Tao · 2017
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Size-independent sample complexity of neural networks
Noah Golowich, Alexander Rakhlin, and Ohad Shamir · 2017
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Learning from noisy singly-labeled data
Ashish Khetan, Zachary C Lipton, and Anima Anandkumar · 2017
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Learning from noisy labels with distillation
Yuncheng Li, Jianchao Yang, Yale Song, Liangliang Cao, Jiebo Luo, and Li-Jia Li · 2017
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Making deep neural networks robust to label noise: A loss correction approach
Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon, Richard Nock, and Lizhen Qu · 2017
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Iterative learning with open-set noisy labels
Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, and Shu-Tao Xia · 2018
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Learning with biased complementary labels
Xiyu Yu, Tongliang Liu, Mingming Gong, and Dacheng Tao · 2018
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Deep unsupervised saliency detection: A multiple noisy labeling perspective
Jing Zhang, Tong Zhang, Yuchao Dai, Mehrtash Harandi, and Richard Hartley · 2018
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Devil is in the edges: Learning semantic boundaries from noisy annotations
David Acuna, Amlan Kar, and Sanja Fidler · 2019
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Deep self-learning from noisy labels
Jiangfan Han, Ping Luo, and Xiaogang Wang · 2019
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A brief introduction to weakly supervised learning
Zhi-Hua Zhou · 2017
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Classification from pairwise similarity and unlabeled data
Han Bao, Gang Niu, and Masashi Sugiyama · 2018
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Co-teaching: Robust training of deep neural networks with extremely noisy labels
Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, and Masashi Sugiyama · 2018
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Learning to cluster in order to transfer across domains and tasks
Yen-Chang Hsu, Zhaoyang Lv, and Zsolt Kira · 2018
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Cleannet: Transfer learning for scalable image classifier training with label noise
Kuang-Huei Lee, Xiaodong He, Lei Zhang, and Linjun Yang · 2018
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Cross-modal ranking with soft consistency and noisy labels for robust rgb-t tracking
Chenglong Li, Chengli Zhu, Yan Huang, Jin Tang, and Liang Wang · 2018
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Foundations of Machine Learning
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar · 2018
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Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser, Phillip Odom, and Zsolt Kira · 2019
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Label-noise robust generative adversarial networks
Takuhiro Kaneko, Yoshitaka Ushiku, and Tatsuya Harada · 2019
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Learning to learn from noisy labeled data
Junnan Li, Yongkang Wong, Qi Zhao, and Mohan S Kankanhalli · 2019
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Takuya Shimada, Han Bao, Issei Sato, and Masashi Sugiyama · 2019
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Learning from noisy labels by regularized estimation of annotator confusion
Ryutaro Tanno, Ardavan Saeedi, Swami Sankaranarayanan, Daniel C Alexander, and Nathan Silberman · 2019
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Symmetric cross entropy for robust learning with noisy labels
Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, and James Bailey · 2019
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Are anchor points really indispensable in label-noise learning?
Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, and Masashi Sugiyama · 2019
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Probabilistic end-to-end noise correction for learning with noisy labels
Kun Yi and Jianxin Wu · 2019
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Metacleaner: Learning to hallucinate clean representations for noisy-labeled visual recognition
Weihe Zhang, Yali Wang, and Yu Qiao · 2019
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