Searching for Robustness: Loss Learning for Noisy Classification Tasks

Searching for Robustness: Loss Learning for Noisy Classification Tasks

IEEE International Conference on Computer Vision (ICCV), 2020

27 February 2021

Timothy M. Hospedales

ArXiv (abs)PDF HTML

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

14 / 14 papers shown

Title
Combating Noisy Labels via Dynamic Connection Masking Xinlei Zhang Fan Liu Chuanyi Zhang Fan Cheng Yuhui Zheng NoLa 252 1 0 13 Aug 2025
Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Richa Upadhyay Ronald Phlypo Rajkumar Saini Marcus Liwicki 273 0 0 21 Jan 2025
Evolving Loss Functions for Specific Image Augmentation TechniquesAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2024 Brandon Morgan Dean Frederick Hougen 186 0 0 09 Apr 2024
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methodsKnowledge and Information Systems (KAIS), 2024 A. Mumuni F. Mumuni 311 14 0 13 Mar 2024
Fast and Efficient Local Search for Genetic Programming Based Loss Function Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang 292 3 0 01 Mar 2024
Neural Loss Function Evolution for Large-Scale Image Classifier Convolutional Neural Networks Brandon Morgan Dean Frederick Hougen 106 4 0 30 Jan 2024
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning Jun Shu Xiang Yuan Deyu Meng Zongben Xu 249 5 0 13 May 2023
Meta-Learning Adaptive Loss Functions Christian Raymond Qi Chen Bing Xue Mengjie Zhang 214 5 0 30 Jan 2023
Improve Noise Tolerance of Robust Loss via Noise-AwarenessIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023 Kehui Ding Jun Shu Deyu Meng Zongben Xu NoLa 251 7 0 18 Jan 2023
Truncate-Split-Contrast: A Framework for Learning from Mislabeled VideosAAAI Conference on Artificial Intelligence (AAAI), 2022 Zixiao Wang Junwu Weng C. Yuan Jue Wang NoLa 205 5 0 27 Dec 2022
Learning Symbolic Model-Agnostic Loss Functions via Meta-LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Christian Raymond Qi Chen Bing Xue Mengjie Zhang FedML 215 14 0 19 Sep 2022
Meta Mirror Descent: Optimiser Learning for Fast Convergence Boyan Gao Henry Gouk Haebeom Lee Timothy M. Hospedales 193 8 0 05 Mar 2022
Meta-Learning in Neural Networks: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 677 2,355 0 11 Apr 2020
Combating noisy labels by agreement: A joint training method with co-regularizationComputer Vision and Pattern Recognition (CVPR), 2020 Jianguo Huang Lei Feng Xiangyu Chen Bo An NoLa 883 617 0 05 Mar 2020