Abstract Details
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Activity Number:
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497
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract #313489
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Title:
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Consistency Analysis of a Convex Clustering Framework
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Author(s):
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Gourab Mukherjee*+ and Peter Radchenko
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Companies:
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University of Southern California and University of Southern California
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Keywords:
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penalized clustering criterion ;
rate of convergence ;
single-cell proteomics ;
class discovery ;
robust clustering
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Abstract:
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We develop a clustering framework based on convex penalties and provide decision theoretic guarantees on its operational characteristics. We compare the rate of converge as well as the population behavior of our convex clustering criterion with those of the \ell_0 penalized clustering criterion. We use regularization path algorithms to demonstrate the applicability of our approach for the detection of cellular subpopulations in single-cell protein expression analysis.
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Authors who are presenting talks have a * after their name.
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