To Smooth or Not? When Label Smoothing Meets Noisy Labels

To Smooth or Not? When Label Smoothing Meets Noisy Labels

8 June 2021

Masashi Sugiyama

Yang Liu

Papers citing "To Smooth or Not? When Label Smoothing Meets Noisy Labels"

7 / 7 papers shown

Title
Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled yet Hard-to-Learn Samples in Noisy Data Weiran Pan Wei Wei Feida Zhu Yong Deng NoLa 88 0 0 24 Apr 2025
Early Stopping Against Label Noise Without Validation Data Suqin Yuan Lei Feng Tongliang Liu NoLa 93 14 0 11 Feb 2025
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels Yaxuan Wang Hao Cheng Jing Xiong Qingsong Wen Han Jia Ruixuan Song L. Zhang Zhaowei Zhu Yang Liu AI4TS 52 1 0 21 Jan 2025
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation Muthuraman Chidambaram Rong Ge AAML 18 0 0 10 Feb 2024
Pseudo-label Correction for Instance-dependent Noise Using Teacher-student Framework Eugene Kim NoLa 20 0 0 24 Nov 2023
Consistency Regularization Can Improve Robustness to Label Noise Erik Englesson Hossein Azizpour NoLa 60 20 0 04 Oct 2021
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 303 494 0 05 Mar 2020