Spectral Clustering

Presentation Summary

In these slides, I present:

• A brief review of k-means, spectral clustering, and graph Laplacians.
• Examples of using k-means and spectral clustering on a toy dataset and on the MNIST handwritten digit dataset.

Examples

• algorithms.py: python script with $k$-means and spectral clustering algorithms that are used in the following iPython notebooks.
• spectral_embedding_toy.ipynb: spectral clustering on toy dataset iPython notebook(html)
• spectral_embedding_mnist.ipynb: spectral clustering on MNIST dataset iPython notebook(html)

References

• A Tutorial on Spectral Clustering, U. von Luxburg (2007)
• scikit-learn Spectral Clustering Doc
• scikit-learn Clustering Overview

All Signal Processing

• by Yubo "Paul" Yang · Compressive Sensing
• by Yubo 'Paul' Yang · Kriging
• by Benjamin Villalonga Correa · Audio Compression
• by Benjamin Villalonga Correa · Pitch Correction
• by Dot Silverman · Crocheting Hypberbolic Surfaces
• by Eli Chertkov · Error Correcting Codes
• by Alex Munoz · Fractal Compression
• by Brian Busemeyer · Compressed sensing
• by Eli Chertkov · Kalman Filter