Sparse Representation and Low-rank Approximation Workshop at NIPS 2011 Invited Talk: Fast Approximation of Matrix Coherence and Statistical Leverage by Michael Mahoney, Stanford University Michael Mahoney is in the math department at Stanford University. Much of his current research focuses on geometric network analysis, i.e., using algorithms with a geometric or statistical flavor to analyze the structure and dynamics of large informatics graphs; developing approximate computation and regularization methods for large informatics graphs; and applications to community detection, clustering, and information dynamics in large social and information networks.
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