Wasserstein Adversarial Regularization (WAR) on label noise

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Wasserstein Adversarial Regularization (WAR) on label noise

8 April 2019

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Papers citing "Wasserstein Adversarial Regularization (WAR) on label noise"

18 / 18 papers shown

Title
Reliable Programmatic Weak Supervision with Confidence Intervals for Label ProbabilitiesIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025 Verónica Álvarez Santiago Mazuelas Steven An Sanjoy Dasgupta 32 0 0 05 Aug 2025
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Han Li Hu Han S.Kevin Zhou 151 0 0 24 May 2025
Improving Noise Robustness through Abstractions and its Impact on Machine Learning Alfredo Ibias Karol Capala Varun Ravi Varma Anna Drozdz José L. R. Sousa AAML 63 1 0 12 Jun 2024
Better, Not Just More: Data-Centric Machine Learning for Earth ObservationIEEE Geoscience and Remote Sensing Magazine (GRSM), 2023 R. Roscher M. Rußwurm Caroline Gevaert Michael C. Kampffmeyer J. A. dos Santos ... Ronny Hansch Stine Hansen Keiller Nogueira Jonathan Prexl D. Tuia 282 20 0 08 Dec 2023
Towards Generalizable Deepfake Detection by Primary Region Regularization Harry Cheng Yangyang Guo Tianyi Wang Liqiang Nie Mohan S. Kankanhalli 177 2 0 24 Jul 2023
Recent Advances in Optimal Transport for Machine LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 Eduardo Fernandes Montesuma Fred-Maurice Ngole-Mboula Antoine Souloumiac OOD OT 186 63 0 28 Jun 2023
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization PathsInternational Conference on Machine Learning (ICML), 2023 Charles Guille-Escuret Hiroki Naganuma Kilian Fatras Ioannis Mitliagkas 122 5 0 20 Jun 2023
Transferring Annotator- and Instance-dependent Transition Matrix for Learning from CrowdsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 Shikun Li Xiaobo Xia Jiankang Deng Shiming Ge Tongliang Liu 188 18 0 05 Jun 2023
Artificial intelligence to advance Earth observation: a perspectiveIEEE Geoscience and Remote Sensing Magazine (GRSM), 2023 D. Tuia Konrad Schindler Begüm Demir Gustau Camps-Valls Xiao Xiang Zhu ... Mihai Datcu Jorge-Arnulfo Quiané-Ruiz Volker Markl Bertrand Le Saux Rochelle Schneider 193 29 0 15 May 2023
PopulAtion Parameter Averaging (PAPA) Alexia Jolicoeur-Martineau Emy Gervais Kilian Fatras Yan Zhang Damien Scieur MoMe 337 24 0 06 Apr 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial RobustnessACM Computing Surveys (ACM Comput. Surv.), 2023 Peiyu Xiong Michael W. Tegegn Jaskeerat Singh Sarin Shubhraneel Pal Julia Rubin SILM AAML 172 13 0 17 Mar 2023
Mitigating Memorization of Noisy Labels by Clipping the Model PredictionInternational Conference on Machine Learning (ICML), 2022 Jianguo Huang Huiping Zhuang Renchunzi Xie Lei Feng Gang Niu Bo An Shouqing Yang VLM NoLa 314 42 0 08 Dec 2022
On making optimal transport robust to all outliers Kilian Fatras OT 110 0 0 23 Jun 2022
Optimal transport meets noisy label robust loss and MixUp regularization for domain adaptation Kilian Fatras Hiroki Naganuma Ioannis Mitliagkas OOD 100 8 0 22 Jun 2022
Meta Optimal TransportInternational Conference on Machine Learning (ICML), 2022 Brandon Amos Samuel N. Cohen Giulia Luise I. Redko OT 203 27 0 10 Jun 2022
Learning to Rectify for Robust Learning with Noisy Labels Haoliang Sun Chenhui Guo Qinglai Wei Zhongyi Han Yilong Yin NoLa 212 40 0 08 Nov 2021
Open-set Label Noise Can Improve Robustness Against Inherent Label NoiseNeural Information Processing Systems (NeurIPS), 2021 Jianguo Huang Lue Tao Renchunzi Xie Bo An NoLa 207 98 0 21 Jun 2021
Combating noisy labels by agreement: A joint training method with co-regularizationComputer Vision and Pattern Recognition (CVPR), 2020 Jianguo Huang Lei Feng Xiangyu Chen Bo An NoLa 719 596 0 05 Mar 2020