v1v2 (latest)

On Symmetric Losses for Learning from Corrupted Labels

27 January 2019

Nontawat Charoenphakdee

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

21 / 71 papers shown

Title
Fair Classification with Group-Dependent Label Noise Jialu Wang Yang Liu Caleb C. Levy NoLa 176 106 0 31 Oct 2020
On the intrinsic robustness to noise of some leading classifiers and symmetric loss function -- an empirical evaluation Hugo Le Baher V. Lemaire Romain Trinquart Polytech Nantes AAML NoLa 109 1 0 22 Oct 2020
Classification with Rejection Based on Cost-sensitive Classification Nontawat Charoenphakdee Zhenghang Cui Yivan Zhang Masashi Sugiyama 254 68 0 22 Oct 2020
Robust Imitation Learning from Noisy Demonstrations Voot Tangkaratt Nontawat Charoenphakdee Masashi Sugiyama NoLa 146 29 0 20 Oct 2020
Importance Reweighting for Biquality Learning Pierre Nodet V. Lemaire A. Bondu Antoine Cornuéjols NoLa 83 6 0 19 Oct 2020
Meta Soft Label Generation for Noisy Labels G. Algan ilkay Ulusoy NoLa 124 42 0 11 Jul 2020
Normalized Loss Functions for Deep Learning with Noisy Labels Xingjun Ma Hanxun Huang Yisen Wang Simone Romano S. Erfani James Bailey NoLa 128 464 0 24 Jun 2020
Learning from Label Proportions: A Mutual Contamination Framework Clayton Scott Jianxin Zhang SSL 81 13 0 12 Jun 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 116 46 0 28 May 2020
Does label smoothing mitigate label noise? Michal Lukasik Srinadh Bhojanapalli A. Menon Surinder Kumar NoLa 269 366 0 05 Mar 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 181 114 0 11 Jan 2020
Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey G. Algan ilkay Ulusoy NoLa VLM 157 346 0 11 Dec 2019
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach Nan Lu Tianyi Zhang Gang Niu Masashi Sugiyama 160 60 0 20 Oct 2019
Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions Clayton Scott Jianxin Zhang 74 7 0 10 Oct 2019
Learning Only from Relevant Keywords and Unlabeled Documents Nontawat Charoenphakdee Jongyeong Lee Yiping Jin Dittaya Wanvarie Masashi Sugiyama 67 10 0 10 Oct 2019
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates Yang Liu Hongyi Guo NoLa 226 248 0 08 Oct 2019
$Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification$ Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification Han Bao Masashi Sugiyama 93 19 0 29 May 2019
Derivative Manipulation for General Example Weighting Xinshao Wang Elyor Kodirov Yang Hua N. Robertson NoLa 240 1 0 27 May 2019
Classification from Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization Takuya Shimada Han Bao Issei Sato Masashi Sugiyama 68 45 0 26 Apr 2019
Noise-tolerant fair classification A. Lamy Ziyuan Zhong A. Menon Nakul Verma NoLa 156 77 0 30 Jan 2019
Complementary-Label Learning for Arbitrary Losses and Models Takashi Ishida Gang Niu A. Menon Masashi Sugiyama VLM 141 118 0 10 Oct 2018