Jahn J (2025)
Publication Type: Journal article
Publication year: 2025
Book Volume: 7
Pages Range: 141-148
Journal Issue: 2
DOI: 10.23952/jano.7.2025.2.01
In the context of unsupervised deep metric learning of image features, Kan, Cen, Mladenovic and He [1] introduced a relative order relation, which is helpful for the comparison of two images in relation to a given special image also called anchor image. This short paper embeds the idea of a relative order relation into a more general mathematical framework. It turns out that this order relation has a strong mathematical structure, which leads to important results on minimality and strong minimality known from vector optimization. Properties of relative order matrices introduced in [1] are also obtained in this general mathematical setting. Among other things, characterizations of strongly minimal objects are given using relative order matrix elements.
APA:
Jahn, J. (2025). SOME NOTES ABOUT A RELATIVE ORDER RELATION USED IN UNSUPERVISED DEEP LEARNING. Journal of Applied and Numerical Optimization, 7(2), 141-148. https://doi.org/10.23952/jano.7.2025.2.01
MLA:
Jahn, Johannes. "SOME NOTES ABOUT A RELATIVE ORDER RELATION USED IN UNSUPERVISED DEEP LEARNING." Journal of Applied and Numerical Optimization 7.2 (2025): 141-148.
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