Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels

14 June 2020

Xiaobo Xia

Bo Han

Nannan Wang

Papers citing "Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels"

9 / 9 papers shown

Title
Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition Jiaming Zhou Hanjun Li Kun-Yu Lin Junwei Liang 23 1 0 28 Nov 2023
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method Manyi Zhang Xuyang Zhao Jun Yao Chun Yuan Weiran Huang 36 20 0 20 Nov 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 21 3 0 11 Oct 2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State Xinshao Wang Yang Hua Elyor Kodirov S. Mukherjee David A. Clifton N. Robertson 19 6 0 30 Jun 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang Li Shen Jian Yang Chen Gong NoLa 27 5 0 27 Jun 2022
Modeling Adversarial Noise for Adversarial Training Dawei Zhou Nannan Wang Bo Han Tongliang Liu AAML 38 15 0 21 Sep 2021
Removing Adversarial Noise in Class Activation Feature Space Dawei Zhou N. Wang Chunlei Peng Xinbo Gao Xiaoyu Wang Jun Yu Tongliang Liu AAML 30 28 0 19 Apr 2021
Provably End-to-end Label-Noise Learning without Anchor Points Xuefeng Li Tongliang Liu Bo Han Gang Niu Masashi Sugiyama NoLa 133 120 0 04 Feb 2021
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 319 498 0 05 Mar 2020