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Sanjoy Dasgupta: Cluster trees, Near-neighbor Graphs, and Continuum Percolation
Thu, Nov 15, 2012 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Sanjoy Dasgupta, UC San Diego
Talk Title: Cluster trees, Near-neighbor Graphs, and Continuum Percolation
Series: CS Colloquium
Abstract: What information does the clustering of a finite data set reveal about the underlying distribution from which the data were sampled? This basic question has proved elusive even for the most widely-used clustering procedures. One natural criterion is to seek clusters that converge (as the data set grows) to regions of high density. When all possible density levels are considered, this is a hierarchical clustering problem where the sought limit is called the "cluster tree". We give a simple algorithm for estimating this tree that implicitly constructs a multiscale hierarchy of near-neighbor graphs on the data points. We show that the procedure is consistent, answering an open problem of Hartigan. We also obtain rates of convergence, using a percolation argument that gives insight into how near-neighbor graphs should be constructed.
Biography: Sanjoy Dasgupta is a Professor in the Department of Computer Science and Engineering at UC San Diego. He received his PhD from Berkeley in 2000, and spent two years at AT&T Research Labs before joining UCSD.
His area of research is algorithmic statistics, with a focus on unsupervised and minimally supervised learning. He is the author of a textbook, "Algorithms" (with Christos Papadimitriou and Umesh Vazirani), that appeared in 2006.
Host: Shaddin Dughmi
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Assistant to CS chair