Equilibrium Distribution for t-Distributed Stochastic Neighbor Embedding with Generalized Kernels

Yi Gu

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arXiv · 2505.24311

Equilibrium Distribution for t-Distributed Stochastic Neighbor Embedding with Generalized Kernels

Yi Gu

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Abstract

T-distributed stochastic neighbor embedding (t-SNE) is a well-known algorithm for visualizing high-dimensional data by finding low-dimensional representations. In this paper, we study the convergence of t-SNE with generalized kernels and extend the results of Auffinger and Fletcher in 2023. Our work starts by giving a concrete formulation of generalized input and output kernels. Then we prove that under certain conditions, the t-SNE algorithm converges to an equilibrium distribution for a wide range of input and output kernels as the number of data points diverges.

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Yi Gu. 2025-05-30. Equilibrium Distribution for t-Distributed Stochastic Neighbor Embedding with Generalized Kernels. https://arxiv.org/abs/2505.24311

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