Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels

10 February 2021

Zhaowei Zhu

Yiwen Song

Yang Liu

NoLa

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Papers citing "Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels"

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Title
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels Yaxuan Wang Hao Cheng Jing Xiong Qingsong Wen Han Jia Ruixuan Song Li Zhang Zhaowei Zhu Yang Liu AI4TS 58 1 0 21 Jan 2025
Noisy Ostracods: A Fine-Grained, Imbalanced Real-World Dataset for Benchmarking Robust Machine Learning and Label Correction Methods Jiamian Hu Yuanyuan Hong Yihua Chen He Wang Moriaki Yasuhara 71 0 0 03 Dec 2024
Label Distribution Shift-Aware Prediction Refinement for Test-Time Adaptation M-U Jang Hye Won Chung TTA 233 0 0 20 Nov 2024
ANNE: Adaptive Nearest Neighbors and Eigenvector-based Sample Selection for Robust Learning with Noisy Labels F. Cordeiro G. Carneiro NoLa 45 1 0 03 Nov 2024
LLM Unlearning via Loss Adjustment with Only Forget Data Yaxuan Wang Jiaheng Wei Chris Liu Jinlong Pang Qiang Liu A. Shah Yujia Bao Yang Liu Wei Wei KELM MU 43 8 0 14 Oct 2024
Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond Minghao Liu Zonglin Di Jiaheng Wei Zhongruo Wang Hengxiang Zhang ... Haobo Wang Lei Feng Jindong Wang James Davis Yang Liu 48 5 0 21 Aug 2024
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions Trenton Chang Jenna Wiens 34 0 0 27 Jun 2024
Measuring Stochastic Data Complexity with Boltzmann Influence Functions Nathan Ng Roger C. Grosse Marzyeh Ghassemi 40 0 0 04 Jun 2024
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning Xinyuan Ji Zhaowei Zhu Wei Xi Olga Gadyatskaya Zilong Song Yong Cai Yang Liu FedML 50 8 0 25 Mar 2024
Skeleton-Based Human Action Recognition with Noisy Labels Yi Xu Kunyu Peng Di Wen Ruiping Liu Junwei Zheng Yufan Chen Jiaming Zhang Alina Roitberg Kailun Yang Rainer Stiefelhagen NoLa 52 3 0 15 Mar 2024
Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards Wei Shen Xiaoying Zhang Yuanshun Yao Rui Zheng Hongyi Guo Yang Liu ALM 40 11 0 12 Mar 2024
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning Heesun Bae Seungjae Shin Byeonghu Na Il-Chul Moon NoLa 46 3 0 05 Mar 2024
Label-Noise Robust Diffusion Models Byeonghu Na Yeongmin Kim Heesun Bae Jung Hyun Lee Seho Kwon Wanmo Kang Il-Chul Moon NoLa DiffM 58 8 0 27 Feb 2024
Measuring and Reducing LLM Hallucination without Gold-Standard Answers Jiaheng Wei Yuanshun Yao Jean-François Ton Hongyi Guo Andrew Estornell Yang Liu HILM 55 18 0 16 Feb 2024
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies Hao Cheng Qingsong Wen Yang Liu Liang Sun OOD AI4TS 13 5 0 03 Feb 2024
Inconsistency-Based Data-Centric Active Open-Set Annotation Ruiyu Mao Ouyang Xu Yunhui Guo 43 4 0 10 Jan 2024
Learning to Complement with Multiple Humans Zheng Zhang Cuong C. Nguyen Kevin Wells Thanh-Toan Do Gustavo Carneiro 29 0 0 22 Nov 2023
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models Zhaowei Zhu Jialu Wang Hao Cheng Yang Liu 29 15 0 19 Nov 2023
Label-free Node Classification on Graphs with Large Language Models (LLMS) Zhikai Chen Haitao Mao Hongzhi Wen Haoyu Han Wei-dong Jin Haiyang Zhang Hui Liu Jiliang Tang 36 75 0 07 Oct 2023
Multi-Label Noise Transition Matrix Estimation with Label Correlations: Theory and Algorithm Shikun Li Xiaobo Xia Han Zhang Shiming Ge Tongliang Liu NoLa 27 0 0 22 Sep 2023
Regularly Truncated M-estimators for Learning with Noisy Labels Xiaobo Xia Pengqian Lu Chen Gong Bo Han Jun-chen Yu Jun Yu Tongliang Liu NoLa 31 9 0 02 Sep 2023
The Importance of Human-Labeled Data in the Era of LLMs Yang Liu ALM 17 8 0 18 Jun 2023
AQuA: A Benchmarking Tool for Label Quality Assessment Mononito Goswami Vedant Sanil Arjun Choudhry Arvind Srinivasan Chalisa Udompanyawit Artur Dubrawski 31 9 0 15 Jun 2023
Transferring Annotator- and Instance-dependent Transition Matrix for Learning from Crowds Shikun Li Xiaobo Xia Jiankang Deng Shiming Ge Tongliang Liu 30 15 0 05 Jun 2023
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks Yuwen Li Miao Xiong Bryan Hooi 18 7 0 30 May 2023
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error Renchunzi Xie Hongxin Wei Lei Feng Yuzhou Cao Bo An OODD OOD 22 10 0 27 Mar 2023
Fairness Improves Learning from Noisily Labeled Long-Tailed Data Jiaheng Wei Zhaowei Zhu Gang Niu Tongliang Liu Sijia Liu Masashi Sugiyama Yang Liu 42 6 0 22 Mar 2023
PASS: Peer-Agreement based Sample Selection for training with Noisy Labels Arpit Garg Cuong C. Nguyen Rafael Felix Thanh-Toan Do G. Carneiro 22 2 0 20 Mar 2023
Learning with Noisy Labels through Learnable Weighting and Centroid Similarity F. Wani Maria Sofia Bucarelli Fabrizio Silvestri NoLa 37 3 0 16 Mar 2023
Latent Class-Conditional Noise Model Jiangchao Yao Bo Han Zhihan Zhou Ya Zhang Ivor W. Tsang NoLa BDL 33 8 0 19 Feb 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach Cuong C. Nguyen Thanh-Toan Do G. Carneiro NoLa 42 0 0 04 Jan 2023
Mitigating Memorization of Noisy Labels by Clipping the Model Prediction Hongxin Wei Huiping Zhuang Renchunzi Xie Lei Feng Gang Niu Bo An Yixuan Li VLM NoLa 26 29 0 08 Dec 2022
Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning Jifeng Hu Yanchao Sun Hechang Chen Sili Huang Haiyin Piao Yi-Ju Chang Lichao Sun 23 5 0 14 Oct 2022
Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes Zhaowei Zhu Yuanshun Yao Jiankai Sun Hanguang Li Yang Liu 34 21 0 06 Oct 2022
Instance-Dependent Noisy Label Learning via Graphical Modelling Arpit Garg Cuong C. Nguyen Rafael Felix Thanh-Toan Do G. Carneiro NoLa 39 27 0 02 Sep 2022
Neighborhood Collective Estimation for Noisy Label Identification and Correction Jichang Li Guanbin Li Feng Liu Yizhou Yu NoLa 30 29 0 05 Aug 2022
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels Ganlong Zhao Guanbin Li Yipeng Qin Feng Liu Yizhou Yu NoLa 33 22 0 29 Jul 2022
ProMix: Combating Label Noise via Maximizing Clean Sample Utility Rui Xiao Yiwen Dong Haobo Wang Lei Feng Runze Wu Gang Chen Jun Zhao 24 54 0 21 Jul 2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State Xinshao Wang Yang Hua Elyor Kodirov S. Mukherjee David A. Clifton N. Robertson 27 6 0 30 Jun 2022
Compressing Features for Learning with Noisy Labels Yingyi Chen S. Hu Xin Shen C. Ai Johan A. K. Suykens NoLa 24 13 0 27 Jun 2022
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets Hongxin Wei Lue Tao Renchunzi Xie Lei Feng Bo An OODD 28 37 0 17 Jun 2022
To Aggregate or Not? Learning with Separate Noisy Labels Jiaheng Wei Zhaowei Zhu Tianyi Luo Ehsan Amid Abhishek Kumar Yang Liu NoLa 41 37 0 14 Jun 2022
Robust Training under Label Noise by Over-parameterization Sheng Liu Zhihui Zhu Qing Qu Chong You NoLa OOD 32 106 0 28 Feb 2022
Identifiability of Label Noise Transition Matrix Yang Liu Hao Cheng Kun Zhang NoLa 38 44 0 04 Feb 2022
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Zhaowei Zhu Jialu Wang Yang Liu NoLa 38 37 0 02 Feb 2022
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations Jiaheng Wei Zhaowei Zhu Weiran Wang Tongliang Liu Gang Niu Yang Liu NoLa 49 242 0 22 Oct 2021
Mitigating Memorization of Noisy Labels via Regularization between Representations Hao Cheng Zhaowei Zhu Xing Sun Yang Liu NoLa 38 28 0 18 Oct 2021
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 149 62 0 12 Oct 2021
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Zhaowei Zhu Tianyi Luo Yang Liu 150 39 0 12 Oct 2021
Instance-dependent Label-noise Learning under a Structural Causal Model Yu Yao Tongliang Liu Biwei Huang Bo Han Gang Niu Kun Zhang CML NoLa 19 68 0 07 Sep 2021