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arxiv 2208.06676 v1 pith:OO72GAKS submitted 2022-08-13 cs.LG

classification cs.LG
keywords methodsadditionalfieldideast-snevectoralongassociated
verification ladder T0 review T1 audit T2 compute T3 formal

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Modern methods in dimensionality reduction are dominated by nonlinear attraction-repulsion force-based methods (this includes t-SNE, UMAP, ForceAtlas2, LargeVis, and many more). The purpose of this paper is to demonstrate that all such methods, by design, come with an additional feature that is being automatically computed along the way, namely the vector field associated with these forces. We show how this vector field gives additional high-quality information and propose a general refinement strategy based on ideas from Morse theory. The efficiency of these ideas is illustrated specifically using t-SNE on synthetic and real-life data sets.

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