Towards Understanding Label Smoothing

Towards Understanding Label Smoothing

20 June 2020

Hao Li

Papers citing "Towards Understanding Label Smoothing"

10 / 10 papers shown

Title
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation Muthuraman Chidambaram Rong Ge AAML 18 0 0 10 Feb 2024
Model Calibration in Dense Classification with Adaptive Label Perturbation Jiawei Liu Changkun Ye Shanpeng Wang Rui-Qing Cui Jing Zhang Kai Zhang Nick Barnes 47 5 0 25 Jul 2023
Rethinking Label Smoothing on Multi-hop Question Answering Zhangyue Yin Yuxin Wang Xiannian Hu Yiguang Wu Hang Yan Xinyu Zhang Zhao Cao Xuanjing Huang Xipeng Qiu 19 9 0 19 Dec 2022
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks C. F. G. Santos João Paulo Papa 22 211 0 10 Jan 2022
Jitter: Random Jittering Loss Function Zhicheng Cai Chenglei Peng S. Du 11 3 0 25 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 32 69 0 08 Jun 2021
Weakly Supervised Label Smoothing Gustavo Penha C. Hauff 11 3 0 15 Dec 2020
Bag of Tricks for Image Classification with Convolutional Neural Networks Tong He Zhi-Li Zhang Hang Zhang Zhongyue Zhang Junyuan Xie Mu Li 221 1,399 0 04 Dec 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,198 0 16 Aug 2016
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,634 0 03 Jul 2012