MD Datamining & Clustering
Purpose: development and analysis of algorithms for data mining, ranking, and clustering with emphasis on linear algebra and optimization methods
Partial List of Topics: data mining, ranking, clustering, recommender systems, methods of singular value decomposition, reverse Simon Ando, kmeans, Fiedler, and nonnegative matrix factorization
Applications: recommender systems, ranking of sports teams, ranking of webpages, clustering of news stories, clustering of social network users.
