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On Symmetric Losses for Learning from Corrupted Labels

27 January 2019

Nontawat Charoenphakdee

Papers citing "On Symmetric Losses for Learning from Corrupted Labels"

50 / 71 papers shown

Title
Learning from Uncertain Similarity and Unlabeled Data Meng Wei Zhongnian Li Peng Ying Xinzheng Xu 0 0 0 15 Sep 2025
On Symmetric Losses for Robust Policy Optimization with Noisy Preferences Soichiro Nishimori Yu Zhang Thanawat Lodkaew Masashi Sugiyama NoLa 72 1 0 30 May 2025
Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel-Young Losses Yuzhou Cao Han Bao Lei Feng Bo An 101 0 0 14 May 2025
Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise Lukasz Sztukiewicz Jack H. Good Artur Dubrawski OOD NoLa 78 1 0 27 May 2024
On the use of Silver Standard Data for Zero-shot Classification Tasks in Information Extraction Jianwei Wang Tianyin Wang Huiping Zhuang 146 3 0 28 Feb 2024
Unified Risk Analysis for Weakly Supervised Learning Chao-Kai Chiang Masashi Sugiyama 113 4 0 15 Sep 2023
Regularly Truncated M-estimators for Learning with Noisy Labels Xiaobo Xia Pengqian Lu Chen Gong Bo Han Jun-chen Yu Jun Yu Tongliang Liu NoLa 116 14 0 02 Sep 2023
Domain Transfer Through Image-to-Image Translation for Uncertainty-Aware Prostate Cancer Classification Meng Zhou A. Jamzad J. Izard A. Menard R. Siemens P. Mousavi MedIm 151 0 0 02 Jul 2023
Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision Yuhao Wu Xiaobo Xia Jun Yu Bo Han Gang Niu Masashi Sugiyama Tongliang Liu 124 3 0 12 Jun 2023
AUC Optimization from Multiple Unlabeled Datasets Zheng Xie Yu Liu Ming Li 190 2 0 25 May 2023
Weakly Supervised AUC Optimization: A Unified Partial AUC Approach Zheng Xie Yu Liu Hao He Ming Li Zhi Zhou NoLa 106 7 0 23 May 2023
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing Tingting Wu Xiao Ding Minji Tang Haotian Zhang Bing Qin Ting Liu NoLa 113 12 0 18 May 2023
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling Dixian Zhu Bokun Wang Zhi Chen Yaxing Wang Milan Sonka Xiaodong Wu Tianbao Yang 191 3 0 14 May 2023
SANTA: Separate Strategies for Inaccurate and Incomplete Annotation Noise in Distantly-Supervised Named Entity Recognition Shuzheng Si Zefan Cai Shuang Zeng Guoqiang Feng Jiaxing Lin Baobao Chang 103 6 0 06 May 2023
Confidence-based Reliable Learning under Dual Noises Peng Cui Yang Yue Zhijie Deng Jun Zhu NoLa 52 8 0 10 Feb 2023
Learning from Stochastic Labels Menglong Wei Zhongnian Li Yong Zhou Qiaoyu Guo Xinzheng Xu 78 0 0 01 Feb 2023
Learning with Silver Standard Data for Zero-shot Relation Extraction Tianyi Wang Jianwei Wang Huiping Zhuang 87 2 0 25 Nov 2022
FeDXL: Provable Federated Learning for Deep X-Risk Optimization Zhishuai Guo Rong Jin Jiebo Luo Tianbao Yang FedML 210 9 0 26 Oct 2022
Performances of Symmetric Loss for Private Data from Exponential Mechanism Jing Bi Vorapong Suppakitpaisarn 33 1 0 09 Oct 2022
Class-Imbalanced Complementary-Label Learning via Weighted Loss Meng Wei Yong Zhou Zhongnian Li Xinzheng Xu 114 14 0 28 Sep 2022
Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning D. Hoang Cuong C. Nguyen Cuong Nguyen anh Belagiannis Vasileios G. Carneiro 121 2 0 17 Aug 2022
Learning from Multiple Annotator Noisy Labels via Sample-wise Label Fusion Zhengqi Gao Fan-Keng Sun Ming-Hsuan Yang Sucheng Ren Zikai Xiong Marc Engeler Antonio Burazer L. Wildling Lucani E. Daniel Duane S. Boning NoLa 123 16 0 22 Jul 2022
Prototype-Anchored Learning for Learning with Imperfect Annotations Xiong Zhou Xianming Liu Deming Zhai Junjun Jiang Xin Gao Xiangyang Ji 70 5 0 23 Jun 2022
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher Jing Jiang Weihong Deng 105 31 0 28 May 2022
Deep Learning with Label Noise: A Hierarchical Approach Li-Wei Chen Ningyuan Huang Cong Mu Hayden S. Helm Kate Lytvynets Weiwei Yang Carey E. Priebe NoLa 89 1 0 28 May 2022
What killed the Convex Booster ? Yishay Mansour Richard Nock Robert C. Williamson 111 1 0 19 May 2022
AUC Maximization in the Era of Big Data and AI: A Survey Tianbao Yang Yiming Ying 269 214 0 28 Mar 2022
Benchmarking Deep AUROC Optimization: Loss Functions and Algorithmic Choices Dixian Zhu Xiaodong Wu Tianbao Yang 140 12 0 27 Mar 2022
Learning with Proper Partial Labels Zheng Wu Jiaqi Lv Masashi Sugiyama 134 10 0 23 Dec 2021
Learning with Label Noise for Image Retrieval by Selecting Interactions Sarah Ibrahimi Arnaud Sors Rafael Sampaio de Rezende Stéphane Clinchant NoLa VLM 104 16 0 20 Dec 2021
The perils of being unhinged: On the accuracy of classifiers minimizing a noise-robust convex loss Philip M. Long Rocco A. Servedio 71 2 0 08 Dec 2021
Robustness and Reliability When Training With Noisy Labels Amanda Olmin Fredrik Lindsten OOD NoLa 96 16 0 07 Oct 2021
Contrastive Representations for Label Noise Require Fine-Tuning Pierre Nodet V. Lemaire A. Bondu Antoine Cornuéjols 54 1 0 20 Aug 2021
Learning with Noisy Labels via Sparse Regularization Xiong Zhou Xianming Liu Chenyang Wang Deming Zhai Junjun Jiang Xiangyang Ji NoLa 133 59 0 31 Jul 2021
Adaptive Sample Selection for Robust Learning under Label Noise Deep Patel P. Sastry OOD NoLa 127 36 0 29 Jun 2021
Asymmetric Loss Functions for Learning with Noisy Labels Xiong Zhou Xianming Liu Junjun Jiang Xin Gao Xiangyang Ji NoLa 100 75 0 06 Jun 2021
An Exploration into why Output Regularization Mitigates Label Noise N. Shoham Tomer Avidor Nadav Tal-Israel NoLa 35 0 0 26 Apr 2021
Do We Really Need Gold Samples for Sample Weighting Under Label Noise? Aritra Ghosh Andrew Lan NoLa 110 11 0 19 Apr 2021
Approximating Instance-Dependent Noise via Instance-Confidence Embedding Yivan Zhang Masashi Sugiyama 87 8 0 25 Mar 2021
Understanding Instance-Level Label Noise: Disparate Impacts and Treatments Yang Liu NoLa 90 36 0 10 Feb 2021
Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization Yivan Zhang Gang Niu Masashi Sugiyama NoLa 127 91 0 04 Feb 2021
A Symmetric Loss Perspective of Reliable Machine Learning Nontawat Charoenphakdee Jongyeong Lee Masashi Sugiyama 122 0 0 05 Jan 2021
From Weakly Supervised Learning to Biquality Learning: an Introduction Pierre Nodet V. Lemaire A. Bondu Antoine Cornuéjols A. Ouorou 129 22 0 16 Dec 2020
A Topological Filter for Learning with Label Noise Pengxiang Wu Songzhu Zheng Mayank Goswami Dimitris N. Metaxas Chao Chen NoLa 126 117 0 09 Dec 2020
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 208 35 0 08 Dec 2020
On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective Nontawat Charoenphakdee J. Vongkulbhisal Nuttapong Chairatanakul Masashi Sugiyama UQCV 82 27 0 18 Nov 2020
Robust Deep Learning with Active Noise Cancellation for Spatial Computing Li Chen David Yang Purvi Goel I. Kabul 87 2 0 16 Nov 2020
High-level Prior-based Loss Functions for Medical Image Segmentation: A Survey Rosana El Jurdia Caroline Petitjean P. Honeine Veronika Cheplygina F. Abdallah SSeg MedIm 114 89 0 16 Nov 2020
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
When Optimizing $f$ -divergence is Robust with Label Noise Jiaheng Wei Yang Liu 142 60 0 07 Nov 2020