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Complementary-Label Learning for Arbitrary Losses and Models

10 October 2018

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

50 / 61 papers shown

Title
Learning from Uncertain Similarity and Unlabeled Data Meng Wei Zhongnian Li Peng Ying Xinzheng Xu 8 0 0 15 Sep 2025
A Unified Empirical Risk Minimization Framework for Flexible N-Tuples Weak Supervision Shuying Huang Junpeng Li Changchun Hua Yana Yang 46 0 0 10 Jul 2025
Realistic Evaluation of Deep Partial-Label Learning Algorithms Wei Wang Dong-Dong Wu Jindong Wang Gang Niu Min Zhang Masashi Sugiyama 105 3 0 17 Feb 2025
Partial-Label Learning with a Reject Option Tobias Fuchs Florian Kalinke Klemens Bohm 186 1 0 08 Jan 2025
Learning from Concealed Labels Zhongnian Li Meng Wei Peng Ying Tongfeng Sun Xinzheng Xu 170 1 0 03 Dec 2024
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes Jiayu Hu Senlin Shu Beibei Li Tao Xiang Zhongshi He 65 0 0 29 Sep 2024
Learning from Complementary Features Kosuke Sugiyama Masato Uchida 192 0 0 27 Aug 2024
Learning from True-False Labels via Multi-modal Prompt Retrieving Zhongnian Li Jinghao Xu Peng Ying Meng Wei Tongfeng Sun 124 0 0 24 May 2024
Rethinking Loss Functions for Fact Verification Yuta Mukobara Yutaro Shigeto Masashi Shimbo AAML 94 0 0 13 Mar 2024
A General Framework for Learning from Weak Supervision Hao Chen Yongfeng Zhang Lei Feng Xiang Li Yidong Wang Xing Xie Masashi Sugiyama Rita Singh Bhiksha Raj 133 6 0 02 Feb 2024
Noisy Correspondence Learning with Self-Reinforcing Errors Mitigation Zhuohang Dang Minnan Luo Chengyou Jia Guangwen Dai Xiao Chang Jingdong Wang 96 10 0 27 Dec 2023
Appeal: Allow Mislabeled Samples the Chance to be Rectified in Partial Label Learning Chongjie Si Xuehui Wang Yan Wang Yunbo Wang Wei Shen 127 1 0 18 Dec 2023
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical Wei Wang Takashi Ishida Yu Zhang Gang Niu Masashi Sugiyama 149 6 0 27 Nov 2023
Unified Risk Analysis for Weakly Supervised Learning Chao-Kai Chiang Masashi Sugiyama 113 4 0 15 Sep 2023
Weakly Supervised Regression with Interval Targets Xi Cheng Yuzhou Cao Ximing Li Bo An Lei Feng 55 6 0 18 Jun 2023
Partial-Label Regression Xin Cheng Deng-Bao Wang Lei Feng Min-Ling Zhang Bo An 62 2 0 15 Jun 2023
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation Weiliang Lin Gang Niu Hsuan-Tien Lin Masashi Sugiyama 68 0 0 15 May 2023
CLImage: Human-Annotated Datasets for Complementary-Label Learning Hsiu-Hsuan Wang Tan-Ha Mai Nai-Xuan Ye Weiliang Lin Hsuan-Tien Lin 147 4 0 15 May 2023
Q&A Label Learning Kota Kawamoto Masato Uchida 64 0 0 08 May 2023
Complementary to Multiple Labels: A Correlation-Aware Correction Approach Yi Gao Miao Xu Min-Ling Zhang 68 1 0 25 Feb 2023
Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides Miriam Hagele Johannes Eschrich Lukas Ruff Maximilian Alber S. Schallenberg A. Guillot C. Roderburg F. Tacke Frederick Klauschen 59 0 0 03 Feb 2023
Learning from Stochastic Labels Menglong Wei Zhongnian Li Yong Zhou Qiaoyu Guo Xinzheng Xu 78 0 0 01 Feb 2023
Rethinking Precision of Pseudo Label: Test-Time Adaptation via Complementary Learning Jiayi Han Longbin Zeng Liang Du Weiyang Ding Jianfeng Feng OOD TTA 109 21 0 15 Jan 2023
Boosting Semi-Supervised Learning with Contrastive Complementary Labeling Qinyi Deng Yong Guo Zhibang Yang Haolin Pan Jian Chen 159 11 0 13 Dec 2022
Complementary Labels Learning with Augmented Classes Zhongnian Li Jian Zhang Mengting Xu Xinzheng Xu Daoqiang Zhang 70 1 0 19 Nov 2022
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks Jianan Zhou Jianing Zhu Jingfeng Zhang Tongliang Liu Gang Niu Bo Han Masashi Sugiyama AAML 76 9 0 01 Nov 2022
Class-Imbalanced Complementary-Label Learning via Weighted Loss Meng Wei Yong Zhou Zhongnian Li Xinzheng Xu 114 14 0 28 Sep 2022
Reduction from Complementary-Label Learning to Probability Estimates Weipeng Lin Hsuan-Tien Lin 123 10 0 20 Sep 2022
Meta Objective Guided Disambiguation for Partial Label Learning B. Zou Ming-Kun Xie Sheng-Jun Huang 96 0 0 26 Aug 2022
ProPaLL: Probabilistic Partial Label Learning Lukasz Struski Jacek Tabor Bartosz Zieliñski 93 2 0 21 Aug 2022
RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning Yue Duan Lei Qi Lei Wang Luping Zhou Yinghuan Shi OOD 84 12 0 09 Aug 2022
Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning Jiachen Du Jialuo Feng Kun-Yu Lin Fa-Ting Hong Xiao-Ming Wu Chen Ma Ying Shan Weihao Zheng 123 6 0 22 Jun 2022
Progressive Purification for Instance-Dependent Partial Label Learning Ning Xu Biao Liu Jiaqi Lv Congyu Qiao Xin Geng 129 19 0 02 Jun 2022
Decompositional Generation Process for Instance-Dependent Partial Label Learning Congyu Qiao Ning Xu Xin Geng 272 86 0 08 Apr 2022
Invariance Learning based on Label Hierarchy S. Toyota Kenji Fukumizu OOD 75 1 0 29 Mar 2022
MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization Yue Duan Zhen Zhao Lei Qi Lei Wang Luping Zhou Yinghuan Shi Yang Gao 107 40 0 27 Mar 2022
Learning with Proper Partial Labels Zheng Wu Jiaqi Lv Masashi Sugiyama 134 10 0 23 Dec 2021
Multi-Class Classification from Single-Class Data with Confidences Yuzhou Cao Lei Feng Senlin Shu Yitian Xu Bo An Gang Niu Masashi Sugiyama 66 3 0 16 Jun 2021
On the Robustness of Average Losses for Partial-Label Learning Jiaqi Lv Biao Liu Lei Feng Ning Xu Miao Xu Bo An Gang Niu Xin Geng Masashi Sugiyama 130 35 0 11 Jun 2021
Leveraged Weighted Loss for Partial Label Learning Hongwei Wen Jingyi Cui H. Hang Jiabin Liu Yisen Wang Zhouchen Lin 99 105 0 10 Jun 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels Jiaheng Wei Hangyu Liu Tongliang Liu Gang Niu Masashi Sugiyama Yang Liu NoLa 244 83 0 08 Jun 2021
An Exploration into why Output Regularization Mitigates Label Noise N. Shoham Tomer Avidor Nadav Tal-Israel NoLa 43 0 0 26 Apr 2021
Lower-Bounded Proper Losses for Weakly Supervised Classification Shuhei M. Yoshida Takashi Takenouchi Masashi Sugiyama 82 2 0 04 Mar 2021
Learning from Similarity-Confidence Data Yuzhou Cao Lei Feng Yitian Xu Bo An Gang Niu Masashi Sugiyama 79 23 0 13 Feb 2021
Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification Nan Lu Shida Lei Gang Niu Issei Sato Masashi Sugiyama 111 16 0 01 Feb 2021
A Survey of Label-noise Representation Learning: Past, Present and Future Bo Han Quanming Yao Tongliang Liu Gang Niu Ivor W. Tsang James T. Kwok Masashi Sugiyama NoLa 161 167 0 09 Nov 2020
Pointwise Binary Classification with Pairwise Confidence Comparisons Lei Feng Senlin Shu Nan Lu Bo Han Miao Xu Gang Niu Bo An Masashi Sugiyama 167 27 0 05 Oct 2020
Learning from a Complementary-label Source Domain: Theory and Algorithms Yiyang Zhang Feng Liu Zhen Fang Bo Yuan Guangquan Zhang Jie Lu 120 71 0 04 Aug 2020
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation Yiyang Zhang Feng Liu Zhen Fang Bo Yuan Guangquan Zhang Jie Lu 116 31 0 29 Jul 2020
Provably Consistent Partial-Label Learning Lei Feng Jiaqi Lv Bo Han Miao Xu Gang Niu Xin Geng Bo An Masashi Sugiyama 91 154 0 17 Jul 2020