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Learning using granularity statistical invariants for classification

Published:2024-04 Issue:8 Volume:54 Page:6667-6681
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Zhu Ting-Ting,Li Chun-Na,Liu Tian,Shao Yuan-Hai

Funder

National Natural Science Foundation of China

ational Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10489-024-05506-x.pdf

Reference47 articles.

1. Pfister N, Bühlmann P, Peters J (2019) Invariant causal prediction for sequential data. J Am Stat Assoc 114(527):1264–1276

2. Masqué JM, Coronado LMP (2020) Parameter-invariant second-order variational problems in one variable. J Phys A: Gen Phys 31(29):6225

3. Chong Y, Peng C, Zhang C, et al (2021) Learning domain invariant and specific representation for cross-domain person re-identification. Applied Intelligence pp 1–14

4. Liu ZQ, Shao YH (2022) Learning using rebalanced statistical invariants for imbalanced classification. Procedia Computer Science 214:203–211

5. Mumuni A, Mumuni F (2021) CNN architectures for geometric transformation-invariant feature representation in computer vision: a review. SN Computer Science 2:1–23

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Granularity Statistical Invariants Learning;2024 International Conference on Artificial Intelligence and Digital Technology (ICAIDT);2024-06-07

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