Department of Mathematics and Statistics
University of Maryland Baltimore County
Contents:
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.
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