Generalized Learning Vector Quantization With Log-Euclidean Metric Learning on Symmetric Positive-Definite Manifold.
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DOI: 10.1109/tcyb.2022.3178412
Abstract: In many classification scenarios, the data to be analyzed can be naturally represented as points living on the curved Riemannian manifold of symmetric positive-definite (SPD) matrices. Due to its non-Euclidean geometry, usual Euclidean learning algorithms… read more here.
Keywords: lem; metric learning; distance; geometry ... See more keywords