Introduction to Clustering Large and High-Dimensional Data

 1. Introduction and motivation; 2. Quadratic k-means algorithm; 3. BIRCH; 4. Spherical k-means algorithm; 5. Linear algebra techniques; 6. Information-theoretic clustering; 7. Clustering with optimization techniques; 8. k-means clustering with divergence; 9. Assessment of clustering results; 10. Appendix: Optimization and Linear Algebra Background; 11. Solutions to selected problems.