Clustering with t-SNE, Provably

DOI10.1137/18M1216134zbMath1499.60259arXiv1706.02582OpenAlexW2963318411WikidataQ100729063 ScholiaQ100729063MaRDI QIDQ5025760

George C. Linderman, Stefan Steinerberger

Publication date: 3 February 2022

Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1706.02582

zbMATH Keywords

maximum principlevisualizationdiscrete dynamical systemspectral clusteringdiscrete elliptic equationt-SNE

Mathematics Subject Classification ID

Nonlinear parabolic equations (35K55) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Diffusion processes (60J60)

Related Items (7)

T-SNE, forceful colorings, and mean field limits ⋮ Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution ⋮ Learning low-dimensional nonlinear structures from high-dimensional noisy data: an integral operator approach ⋮ Randomized near-neighbor graphs, giant components and applications in data science ⋮ Unnamed Item ⋮ Numerical integration on graphs: Where to sample and how to weigh ⋮ Dimensionality Reduction via Dynamical Systems: The Case of t-SNE

Uses Software

• t-SNE

Cites Work

• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
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