Detecting Corrupted Labels Without Training a Model to Predict

Detecting Corrupted Labels Without Training a Model to Predict

12 October 2021

Zhaowei Zhu

Yang Liu

Papers citing "Detecting Corrupted Labels Without Training a Model to Predict"

11 / 11 papers shown

Title
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs Shenzhi Yang Bin Liang An Liu Lin Gui Xingkai Yao Xiaofang Zhang OODD 69 3 0 18 Apr 2025
An Embedding is Worth a Thousand Noisy Labels Francesco Di Salvo Sebastian Doerrich Ines Rieger Christian Ledig NoLa 73 0 0 26 Aug 2024
Inconsistency-Based Data-Centric Active Open-Set Annotation Ruiyu Mao Ouyang Xu Yunhui Guo 40 3 0 10 Jan 2024
Fairness Improves Learning from Noisily Labeled Long-Tailed Data Jiaheng Wei Zhaowei Zhu Gang Niu Tongliang Liu Sijia Liu Masashi Sugiyama Yang Liu 36 6 0 22 Mar 2023
Learning with Noisy Labels through Learnable Weighting and Centroid Similarity F. Wani Maria Sofia Bucarelli Fabrizio Silvestri NoLa 34 3 0 16 Mar 2023
Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei Renchunzi Xie Hao-Ran Cheng Lei Feng Bo An Yixuan Li OODD 163 266 0 19 May 2022
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Zhaowei Zhu Jialu Wang Yang Liu NoLa 32 37 0 02 Feb 2022
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Zhaowei Zhu Tianyi Luo Yang Liu 150 39 0 12 Oct 2021
Provably End-to-end Label-Noise Learning without Anchor Points Xuefeng Li Tongliang Liu Bo Han Gang Niu Masashi Sugiyama NoLa 130 120 0 04 Feb 2021
Federated Bandit: A Gossiping Approach Zhaowei Zhu Jingxuan Zhu Ji Liu Yang Liu FedML 139 83 0 24 Oct 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 313 498 0 05 Mar 2020