Learning to Purify Noisy Labels via Meta Soft Label Corrector

3 August 2020

Papers citing "Learning to Purify Noisy Labels via Meta Soft Label Corrector"

10 / 10 papers shown

Title
Mitigating Label Noise through Data Ambiguation Julian Lienen Eyke Hüllermeier NoLa 32 7 0 23 May 2023
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning Jun Shu Xiang Yuan Deyu Meng Zongben Xu 28 4 0 13 May 2023
Learning from Noisy Labels with Decoupled Meta Label Purifier Yuanpeng Tu Boshen Zhang Yuxi Li Liang Liu Jian Li Yabiao Wang Chengjie Wang C. Zhao NoLa 49 27 0 14 Feb 2023
Improve Noise Tolerance of Robust Loss via Noise-Awareness Kehui Ding Jun Shu Deyu Meng Zongben Xu NoLa 33 5 0 18 Jan 2023
Class-Level Logit Perturbation Mengyang Li Fengguang Su O. Wu Tianjin University AAML 31 3 0 13 Sep 2022
Gradient-based Bi-level Optimization for Deep Learning: A Survey Can Chen Xiangshan Chen Chen Ma Zixuan Liu Xue Liu 94 35 0 24 Jul 2022
L2B: Learning to Bootstrap Robust Models for Combating Label Noise Yuyin Zhou Xianhang Li Fengze Liu Qingyue Wei Xuxi Chen Lequan Yu Cihang Xie M. Lungren Lei Xing NoLa 47 3 0 09 Feb 2022
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 110 717 0 13 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 377 11,700 0 09 Mar 2017
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 270 1,275 0 06 Mar 2017