Computer Science > Machine Learning
arXiv:2408.00483 (cs)
[Submitted on 1 Aug 2024]
Title:A Systematic Review on Long-Tailed Learning
Authors:Chongsheng Zhang,George Almpanidis,Gaojuan Fan,Binquan Deng,Yanbo Zhang,Ji Liu,Aouaidjia Kamel,Paolo Soda,João Gama
View a PDF of the paper titled A Systematic Review on Long-Tailed Learning, by Chongsheng Zhang and 8 other authors
View PDFHTML (experimental)Abstract:Long-tailed data is a special type of multi-class imbalanced data with a very large amount of minority/tail classes that have a very significant combined influence. Long-tailed learning aims to build high-performance models on datasets with long-tailed distributions, which can identify all the classes with high accuracy, in particular the minority/tail classes. It is a cutting-edge research direction that has attracted a remarkable amount of research effort in the past few years. In this paper, we present a comprehensive survey of latest advances in long-tailed visual learning. We first propose a new taxonomy for long-tailed learning, which consists of eight different dimensions, including data balancing, neural architecture, feature enrichment, logits adjustment, loss function, bells and whistles, network optimization, and post hoc processing techniques. Based on our proposed taxonomy, we present a systematic review of long-tailed learning methods, discussing their commonalities and alignable differences. We also analyze the differences between imbalance learning and long-tailed learning approaches. Finally, we discuss prospects and future directions in this field.
| Comments: | Current Under Revision at IEEE TNNLS. [This is the long/Full-length version of our Long-Tailed Learning Survey paper] |
| Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Multimedia (cs.MM) |
| Cite as: | arXiv:2408.00483 [cs.LG] |
| (orarXiv:2408.00483v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2408.00483 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled A Systematic Review on Long-Tailed Learning, by Chongsheng Zhang and 8 other authors
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