Normalized Loss Functions for Deep Learning with Noisy Labels

24 June 2020

Papers citing "Normalized Loss Functions for Deep Learning with Noisy Labels"

50 / 220 papers shown

Title
MonoBox: Tightness-free Box-supervised Polyp Segmentation using Monotonicity Constraint Qiang Hu Zhenyu Yi Ying Zhou Ting Li Fan Huang Mei Liu Qiang Li Zhiwei Wang 113 4 0 01 Apr 2024
Group Benefits Instances Selection for Data Purification Zhenhuang Cai Chuanyi Zhang Dan Huang Yuanbo Chen Xiuyun Guan Yazhou Yao NoLa 110 0 0 23 Mar 2024
A Unified Optimal Transport Framework for Cross-Modal Retrieval with Noisy Labels Haocheng Han Minnan Luo Huan Liu Fang Nan 105 0 0 20 Mar 2024
Skeleton-Based Human Action Recognition with Noisy Labels Yi Xu Kunyu Peng Di Wen Ruiping Liu Junwei Zheng Yufan Chen Kailai Li Alina Roitberg Kailun Yang Rainer Stiefelhagen NoLa 103 5 0 15 Mar 2024
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning Heesun Bae Seungjae Shin Byeonghu Na Il-Chul Moon NoLa 127 6 0 05 Mar 2024
On the use of Silver Standard Data for Zero-shot Classification Tasks in Information Extraction Jianwei Wang Tianyin Wang Huiping Zhuang 146 3 0 28 Feb 2024
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies Hao Cheng Qingsong Wen Yang Liu Liang Sun OOD AI4TS 94 9 0 03 Feb 2024
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels Chen-Chen Zong Ye-Wen Wang Ming-Kun Xie Sheng-Jun Huang 127 8 0 13 Jan 2024
Robust Loss Functions for Training Decision Trees with Noisy Labels Jo Wilton Nan Ye NoLa 112 5 0 20 Dec 2023
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision Collin Burns Pavel Izmailov Jan Hendrik Kirchner Bowen Baker Leo Gao ... Adrien Ecoffet Manas Joglekar Jan Leike Ilya Sutskever Jeff Wu ELM 188 323 0 14 Dec 2023
ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance Ling-Hao Chen Yuanshuo Zhang Taohua Huang Liangcai Su Zeyi Lin Xi Xiao Xiaobo Xia Tongliang Liu NoLa 172 11 0 13 Dec 2023
A Unified Framework for Connecting Noise Modeling to Boost Noise Detection Siqi Wang Chau Pham Bryan A. Plummer NoLa 108 0 0 30 Nov 2023
Overcoming Label Noise for Source-free Unsupervised Video Domain Adaptation A. Dasgupta C. V. Jawahar Karteek Alahari TTA VLM 123 12 0 30 Nov 2023
Are Ensembles Getting Better all the Time? Pierre-Alexandre Mattei Damien Garreau OOD FedML 168 1 0 29 Nov 2023
Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints Xiaobo Xia Jiale Liu Shaokun Zhang Qingyun Wu Hongxin Wei Tongliang Liu 166 14 0 15 Nov 2023
Noisy Pair Corrector for Dense Retrieval Hang Zhang Yeyun Gong Xingwei He Dayiheng Liu Daya Guo Jiancheng Lv Jian Guo 97 8 0 07 Nov 2023
Resist Label Noise with PGM for Graph Neural Networks Qingqing Ge Jianxiang Yu Zeyuan Zhao Xiang Li NoLa AAML 90 0 0 03 Nov 2023
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy Dongmin Park Seola Choi Doyoung Kim Hwanjun Song Jae-Gil Lee NoLa 150 25 0 02 Nov 2023
Cross-modal Active Complementary Learning with Self-refining Correspondence Yang Qin Yuan Sun Dezhong Peng Qiufeng Wang Xiaocui Peng Peng Hu 130 28 0 26 Oct 2023
Robust-GBDT: GBDT with Nonconvex Loss for Tabular Classification in the Presence of Label Noise and Class Imbalance Jiaqi Luo Yuedong Quan Shixin Xu 120 2 0 08 Oct 2023
Quantifying and mitigating the impact of label errors on model disparity metrics Julius Adebayo Melissa Hall Bowen Yu Bobbie Chern 86 11 0 04 Oct 2023
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks Hao Chen Yongfeng Zhang Ankit Shah Ran Tao Jianguo Huang Berfin cSimcsek Masashi Sugiyama Bhiksha Raj 151 35 0 29 Sep 2023
Neural network-based coronary dominance classification of RCA angiograms Ivan Kruzhilov Egor Ikryannikov Artem Shadrin Ruslan Utegenov Galina Zubkova Ivan Bessonov 30 4 0 13 Sep 2023
KD-FixMatch: Knowledge Distillation Siamese Neural Networks Chi Wang Shaoyuan Xu Jinmiao Fu Yang Liu Bryan Wang 49 0 0 11 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 116 14 0 02 Sep 2023
Channel-Wise Contrastive Learning for Learning with Noisy Labels Hui-Sung Kang Sheng Liu Huaxi Huang Tongliang Liu NoLa 106 0 0 14 Aug 2023
Curriculum Guided Domain Adaptation in the Dark C. S. Jahan Andreas E. Savakis 114 3 0 02 Aug 2023
Sparse Double Descent in Vision Transformers: real or phantom threat? Victor Quétu Marta Milovanović Enzo Tartaglione 165 2 0 26 Jul 2023
Label Noise: Correcting a Correction William Toner Amos Storkey NoLa 138 0 0 24 Jul 2023
Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels? Cheng-En Wu Yu Tian Haichao Yu Heng Wang Pedro Morgado Yu Hen Hu Linjie Yang NoLa VPVLM VLM 80 23 0 22 Jul 2023
Learning to Segment from Noisy Annotations: A Spatial Correction Approach Jiacheng Yao Yikai Zhang Songzhu Zheng Mayank Goswami Prateek Prasanna Chao Chen 110 19 0 21 Jul 2023
Differences Between Hard and Noisy-labeled Samples: An Empirical Study Mahsa Forouzesh Patrick Thiran NoLa 85 3 0 20 Jul 2023
GenKL: An Iterative Framework for Resolving Label Ambiguity and Label Non-conformity in Web Images Via a New Generalized KL Divergence Xia Huang Kai Fong Ernest Chong 98 4 0 19 Jul 2023
Mitigating Label Bias via Decoupled Confident Learning Yunyi Li Maria De-Arteaga M. Saar-Tsechansky 92 0 0 18 Jul 2023
Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels Hui-Sung Kang Sheng Liu Huaxi Huang Jun Yu Bo Han Dadong Wang Tongliang Liu NoLa 105 4 0 11 Jul 2023
Leveraging an Alignment Set in Tackling Instance-Dependent Label Noise Donna Tjandra Jenna Wiens NoLa 96 4 0 10 Jul 2023
Validation of the Practicability of Logical Assessment Formula for Evaluations with Inaccurate Ground-Truth Labels Yongquan Yang Hong Bu 115 0 0 06 Jul 2023
LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration Siqi Wang Bryan A. Plummer 121 2 0 20 Jun 2023
MILD: Modeling the Instance Learning Dynamics for Learning with Noisy Labels Chuanyan Hu Shipeng Yan Zhitong Gao Xuming He NoLa 116 5 0 20 Jun 2023
FedNoisy: Federated Noisy Label Learning Benchmark Siqi Liang Jintao Huang Junyuan Hong Dun Zeng Jiayu Zhou Zenglin Xu FedML 271 8 0 20 Jun 2023
Robust T-Loss for Medical Image Segmentation Alvaro Gonzalez-Jimenez Simone Lionetti Philippe Gottfrois Fabian Gröger Marc Pouly Alexander A. Navarini OOD 150 16 0 01 Jun 2023
Instance-dependent Noisy-label Learning with Graphical Model Based Noise-rate Estimation Arpit Garg Cuong C. Nguyen Rafael Felix Thanh-Toan Do G. Carneiro NoLa 123 1 0 31 May 2023
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling Yuchen Zhuang Yue Yu Lingkai Kong Xiang Chen Chao Zhang NoLa SyDa AI4CE 133 17 0 30 May 2023
CoLaDa: A Collaborative Label Denoising Framework for Cross-lingual Named Entity Recognition Tingting Ma Qianhui Wu Huiqiang Jiang Börje F. Karlsson Tiejun Zhao Chin-Yew Lin 106 8 0 24 May 2023
Mitigating Label Noise through Data Ambiguation Julian Lienen Eyke Hüllermeier NoLa 105 7 0 23 May 2023
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations Hao Chen Ankit Shah Yongfeng Zhang R. Tao Yidong Wang Xingxu Xie Masashi Sugiyama Rita Singh Bhiksha Raj 152 13 0 22 May 2023
Enhancing Contrastive Learning with Noise-Guided Attack: Towards Continual Relation Extraction in the Wild Ting Wu Jingyi Liu Rui Zheng Tao Gui Tao Gui Xuanjing Huang CLL 96 3 0 11 May 2023
A Curriculum View of Robust Loss Functions Zebin Ou Yue Zhang NoLa 108 0 0 03 May 2023
Compensation Learning in Semantic Segmentation Timo Kaiser Christoph Reinders Bodo Rosenhahn NoLa 89 5 0 26 Apr 2023
Implicit Counterfactual Data Augmentation for Robust Learning Xiaoling Zhou Ou Wu Michael K. Ng CML OOD BDL 153 2 0 26 Apr 2023