1.11 《A Second-Order Approach to Learning with Instance-Dependent Label Noise》 This paper propose a second-order approach with the assistance of additional second-order statistics and explore how this information can improve the robustness of learning with instance-dependent label noise. Paper link:...
Deep Learning with Noisy Label 背景理想状态下,深度学习依赖大量高质量标注,时间&人力成本高往往数据标注质量往往并不处于理想状态,噪声不可避免算法分类基于噪声模型的方法:把分类器和噪声隔离开,希望通过噪声… 资瓷向量机发表于搬砖杂记 [CVPR2023] Twin Contrastive Learning with Noisy Labels Breann Introductio...
Learning with Instance-Dependent Label Noise: A Sample Sieve ApproachHao ChengZhaowei ZhuXingyu LiYifei GongXing SunYang LiuInternational Conference on Learning Representations
This code is a PyTorch implementation of our paper "Learning with Instance-Dependent Label Noise: A Sample Sieve Approach" accepted by ICLR2021. The code is run on the Tesla V-100. Prerequisites Python 3.6.9 PyTorch 1.2.0 Torchvision 0.5.0 ...
2020-ICML - Learning with Bounded Instance-and Label-dependent Label Noise.[Paper] 2020-ICML - Label-Noise Robust Domain Adaptation.[Paper] 2020-ICML - LTF: A Label Transformation Framework for Correcting Label Shift.[Papeer] 2020-ICML - Does label smoothing mitigate label noise?.[Paper] ...
Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2010] proved that under symmetric label noise (SLN), minimisation of any convex potential over a linear function class can result in classification performance equivalent to random guessing. Thi...
For instance, the user gives a wrong learning example to the system by commanding "Turn on the television!" and pushing a power button on the wrong remote control. The spoken command is then supervised by a wrong action and we refer to these errors as label noise. Secondly, the mapping ...
Similarly, when class labels are corrupted by mislabeled instances, methods are needed for learning in the presence of class label noise (LN). Here we propose adaptive sampling (AdaSampling), a framework for both PU learning and learning with class LN. By iteratively estimating the class mis...
上述将两类进行置换的情况叫做pairwise label noise,再引申一下: Symmetry Label Noise:通过将给定比例的训练样本的标签统一翻转到其他类标签之一来生成对称噪声标签。 综合起来,我们举一个Co-teaching论文里面的例子: 2) Instance-dependent Label Noise 样本相关的噪声,即样本标签的噪声和样本本身的特征有关, “你妈...
Instance-Dependent Label-Noise Learning under Structural Causal Models. NeurIPS'21作者:Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang [Weakly Supervised Learning] & [Stru…