A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges
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DOI: 10.1016/j.neucom.2020.08.017
Abstract: Abstract Distance metric learning is a branch of machine learning that aims to learn distances from the data, which enhances the performance of similarity-based algorithms. This tutorial provides a theoretical background and foundations on this… read more here.
Keywords: distance metric; mathematical foundations; metric learning; experimental analysis ... See more keywords
Divergence Measures: Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
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DOI: 10.3390/e24050712
Abstract: Data science, information theory, probability theory, statistical learning, statistical signal processing, and other related disciplines greatly benefit from non-negative measures of dissimilarity between pairs of probability measures [...]. read more here.
Keywords: information; measures mathematical; foundations applications; divergence measures ... See more keywords
Symmetries in Dynamic Models of Biological Systems: Mathematical Foundations and Implications
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DOI: 10.3390/sym14030467
Abstract: Symmetries are ubiquitous in nature. Almost all organisms have some kind of “symmetry”, meaning that their shape does not change under some geometric transformation. This geometrical concept of symmetry is intuitive and easy to recognize.… read more here.
Keywords: symmetries dynamic; dynamic models; systems mathematical; biological systems ... See more keywords