by Eli Chertkov

# Spectral Clustering

Identifying clusters in data using linear algebra and graph theory.

## 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**

Yubo "Paul" Yang ALGORITHM

clustering, data analysis