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A multiscale environment for learning by diffusion

  • Published:2022-03 Issue: Volume:57 Page:58-100
  • ISSN:1063-5203
  • Container-title:Applied and Computational Harmonic Analysis
  • language:en
  • Short-container-title:Applied and Computational Harmonic Analysis

Author:

Murphy James M.,Polk Sam L.ORCID

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference71 articles.

1. Link communities reveal multiscale complexity in networks;Ahn;Nature,2010

2. Clustering based on pairwise distances when the data is of mixed dimensions;Arias-Castro;IEEE Trans. Inf. Theory,2011

3. Spectral clustering based on local linear approximations;Arias-Castro;Electron. J. Stat.,2011

4. Spectral clustering based on local PCA;Arias-Castro;J. Mach. Learn. Res.,2017

5. K-means++: the advantages of careful seeding;Arthur,2006

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1. Unsupervised Behavior Inference From Human Action Sequences;2024 IEEE Conference on Games (CoG);2024-08-05

2. Superpixel-Based and Spatially Regularized Diffusion Learning for Unsupervised Hyperspectral Image Clustering;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Time-Inhomogeneous Diffusion Geometry and Topology;SIAM Journal on Mathematics of Data Science;2023-05-22

4. Unsupervised Diffusion and Volume Maximization-Based Clustering of Hyperspectral Images;Remote Sensing;2023-02-15

5. Unsupervised Spatial-Spectral Hyperspectral Image Reconstruction And Clustering With Diffusion Geometry;2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS);2022-09-13
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