memorization effect

Do We Need to Penalize Variance of Losses for Learning with Label Noise? JMLR 2026 Partially Blinded Unlearning: Class Unlearning for Deep Networks from Bayesian Perspective AAAI 2025 IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples AAAI 2024 Learning with Structural Labels for Learning with Noisy Labels CVPR 2024 Mitigating Label Noise through Data Ambiguation AAAI 2024 Mitigating Memorization of Noisy Labels via Regularization between Representations ICLR 2023 Contrastive Learning with Boosted Memorization ICML 2022 Large Loss Matters in Weakly Supervised Multi-Label Classification CVPR 2022 Learning With Twin Noisy Labels for Visible-Infrared Person Re-Identification CVPR 2022 LOPS: Learning Order Inspired Pseudo-Label Selection for Weakly Supervised Text Classification EMNLP 2022 RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning NeurIPS 2022 The Role of Deconfounding in Meta-learning ICML 2022 Jo-SRC: A Contrastive Approach for Combating Noisy Labels CVPR 2021 Me-Momentum: Extracting Hard Confident Examples From Noisily Labeled Data ICCV 2021 Understanding and Improving Early Stopping for Learning with Noisy Labels NeurIPS 2021 Searching to Exploit Memorization Effect in Learning with Noisy Labels ICML 2020 Co-teaching: Robust training of deep neural networks with extremely noisy labels NeurIPS 2018