arXiv stat.ML
· Papers
Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality Reduction
arXiv:2502.00168v5 Announce Type: replace Abstract: Supervised dimensionality reduction maps labeled data into a low-dimensional feature space while preserving class separation. A common strategy is to learn features that maximize a measure of statistical dissimilarity between the class-conditional probability distribu