Parametric UMAP Embeddings for Representation and Semisupervised Learning
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DOI: 10.1162/neco_a_01434
Abstract: Abstract UMAP is a nonparametric graph-based dimensionality reduction algorithm using applied Riemannian geometry and algebraic topology to find low-dimensional embeddings of structured data. The UMAP algorithm consists of two steps: (1) computing a graphical representation… read more here.
Keywords: learning parametric; parametric umap; umap embeddings; embeddings representation ... See more keywords