AI News Hub Logo

AI News Hub

Some Theoretical Limitations of t-SNE

cs.LG updates on arXiv.org
Rupert Li, Elchanan Mossel

arXiv:2604.13295v1 Announce Type: new Abstract: t-SNE has gained popularity as a dimension reduction technique, especially for visualizing data. It is well-known that all dimension reduction techniques may lose important features of the data. We provide a mathematical framework for understanding this loss for t-SNE by establishing a number of results in different scenarios showing how important features of data are lost by using t-SNE.