Measure-based diffusion grid construction and high-dimensional data discretization-Reference-Cited by-同舟云学术

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Measure-based diffusion grid construction and high-dimensional data discretization

Published:2016-03 Issue:2 Volume:40 Page:207-228
ISSN:1063-5203
Container-title:Applied and Computational Harmonic Analysis
language:en
Short-container-title:Applied and Computational Harmonic Analysis

Author:

Bermanis Amit,Salhov Moshe,Wolf Guy,Averbuch Amir

Funder

Israel Science Foundation

Israeli Ministry of Science & Technology

US–Israel Binational Science Foundation

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference27 articles.

1. Laplacian eigenmaps for dimensionality reduction and data representation;Belkin;Neural Comput.,2003

2. A. Bermanis, G. Wolf, A. Averbuch, Diffusion-based kernel methods on Euclidean metric measure spaces, 2012, submitted for publication.

3. Measure-based diffusion kernel methods;Bermanis,2013

4. Diffusion maps;Coifman;Appl. Comput. Harmon. Anal.,2006

5. Multidimensional Scaling;Cox,1994

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Convergence of graph Laplacian with kNN self-tuned kernels;Information and Inference: A Journal of the IMA;2021-09-27

2. Diffusion representations;Applied and Computational Harmonic Analysis;2018-09

3. Diffusion-based kernel methods on Euclidean metric measure spaces;Applied and Computational Harmonic Analysis;2016-07

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