Searching for Robustness: Loss Learning for Noisy Classification Tasks

27 February 2021

Papers citing "Searching for Robustness: Loss Learning for Noisy Classification Tasks"

9 / 9 papers shown

Title
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods A. Mumuni F. Mumuni 70 5 0 13 Mar 2024
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
Online Loss Function Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang 30 5 0 30 Jan 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
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang FedML 29 11 0 19 Sep 2022
Meta Mirror Descent: Optimiser Learning for Fast Convergence Boyan Gao Henry Gouk Haebeom Lee Timothy M. Hospedales 24 6 0 05 Mar 2022
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 103 34 0 08 Dec 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 46 1,928 0 11 Apr 2020
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