A tractable latent variable model for nonlinear dimensionality reduction

DOI10.1073/pnas.1916012117zbMath1485.68241OpenAlexW3035929102WikidataQ96640097 ScholiaQ96640097MaRDI QIDQ5073081

Lawrence K. Saul

Publication date: 5 May 2022

Published in: Proceedings of the National Academy of Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1073/pnas.1916012117

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Computational aspects of data analysis and big data (68T09)

Cites Work

• EM algorithms for ML factor analysis
• Nearly Linear Time Algorithms for Preconditioning and Solving Symmetric, Diagonally Dominant Linear Systems
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
• A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
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