Complementary-Label Learning for Arbitrary Losses and Models

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Complementary-Label Learning for Arbitrary Losses and Models

10 October 2018

Masashi Sugiyama

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Papers citing "Complementary-Label Learning for Arbitrary Losses and Models"

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Title
Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology Hiroki Tokunaga Brian Kenji Iwana Y. Teramoto Akihiko Yoshizawa Ryoma Bise 165 18 0 16 Jul 2020
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels Yu-Ting Chou Gang Niu Hsuan-Tien Lin Masashi Sugiyama 179 62 0 05 Jul 2020
Do We Need Zero Training Loss After Achieving Zero Training Error? Takashi Ishida Ikko Yamane Tomoya Sakai Gang Niu Masashi Sugiyama AI4CE 103 142 0 20 Feb 2020
Progressive Identification of True Labels for Partial-Label Learning Jiaqi Lv Miao Xu Lei Feng Gang Niu Xin Geng Masashi Sugiyama 197 189 0 19 Feb 2020
Bridging Ordinary-Label Learning and Complementary-Label Learning Yasuhiro Katsura M. Uchida FedML CLL 84 19 0 06 Feb 2020
Learning with Multiple Complementary Labels Lei Feng Takuo Kaneko Bo Han Gang Niu Bo An Masashi Sugiyama 185 105 0 30 Dec 2019
Simplified and Unified Analysis of Various Learning Problems by Reduction to Multiple-Instance Learning D. Suehiro Eiji Takimoto 89 1 0 14 Nov 2019
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach Nan Lu Tianyi Zhang Gang Niu Masashi Sugiyama 184 60 0 20 Oct 2019
Learning from Indirect Observations Yivan Zhang Nontawat Charoenphakdee Masashi Sugiyama 91 5 0 10 Oct 2019
Generative-Discriminative Complementary Learning Yanwu Xu Biwei Huang Junxiang Chen Tongliang Liu Kun Zhang Kayhan Batmanghelich GAN 167 39 0 02 Apr 2019
Binary Classification from Positive-Confidence Data Takashi Ishida Gang Niu Masashi Sugiyama 116 60 0 19 Oct 2017