# Quantifying Local and Global Fidelity of Nonlinear Embeddings

**Published:** November 3, 2026
**Author:** Henry Han
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/en/articles/quantifying-local-and-global-fidelity-of-nonlinear-embeddings

arXiv:2611.00290v1 Announce Type: new Abstract: Dimension reduction methods are chosen by a common claim: t-SNE and UMAP preserve local structure, and PCA preserves global structure. Checking it on given data takes local and global scores on one scale and a test that compares…

> From the original source: **arXiv — cs.AI**
> [Read full article at arXiv — cs.AI](https://arxiv.org/abs/2611.00290)

**Tags:** #arXiv

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