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Similarity Based on Resample Exposure
Measuring distance and similarity is one of the most fundamental problems in data science and statistics. Proximity functions are used almost everywhere, from clustering problems to outlier detection, database systems, and data privacy. One important challenge is how to handle heterogeneous data, which makes up a large part of real-world tabular data ...Anton Danholt Lautrup +5 more
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A semi-supervised resampling method for class-imbalanced learning
Expert Systems With Applications, 2023Zhen Jiang, Yongzhao Zhan, Qirong Mao
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Redistribution Networks for Resampling
2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2023Michael Lunglmayr, Víctor Elvira
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Impact of resampling methods and classification models on the imbalanced credit scoring problems
Information Sciences, 2021Ling Xie, Jin Xiao, Yadong Wang
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An Evaluation of Four Resampling Methods Used in Machine Learning Classification
IEEE Intelligent Systems, 2021Robbie Nakatsu
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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Michael Bernasconi +4 more
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Michael Bernasconi +4 more
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On the robustness of JPEG post-compression to resampling factor estimation
Signal Processing, 2020Yijun Mao, Wei Lu, Qin Zhang
exaly