Scalable Spectral Clustering With Nyström Approximation: Practical and Theoretical Aspects

Scalable Spectral Clustering With Nyström Approximation: Practical and Theoretical Aspects

Spectral clustering techniques are valuable tools in signal processing and machine learning for partitioning complex data sets. The effectiveness of spectral clustering stems from constructing a non-linear embedding based on creating a similarity graph and computing the spectral decomposition of the...

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Bibliographic Details
Main Author: Farhad Pourkamali-Anaraki
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Open Journal of Signal Processing
Subjects:
Approximation methods
clustering algorithms
computational complexity
sampling methods
Online Access:https://ieeexplore.ieee.org/document/9264745/

Internet

https://ieeexplore.ieee.org/document/9264745/

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