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Activity Number:
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523
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract #320687
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View Presentation
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Title:
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Non-Negative Rank and the EM Algorithm
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Author(s):
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Elina Robeva* and Kaie Kubjas and Bernd Sturmfels
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Companies:
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University of California at Berkeley and Aalto University and University of California at Berkeley
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Keywords:
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mixture models ;
nonnegative rank ;
algebraic geometry
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Abstract:
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Mixtures of r independent distributions for two discrete random variables can be represented by matrices of nonnegative rank r. Likelihood inference for the model of such joint distributions leads to problems in real algebraic geometry that we address here. We characterize the set of fixed points of the Expectation-Maximization algorithm, and we study the boundary of the space of matrices with nonnegative rank at most 3. Both of these sets correspond to algebraic varieties with many irreducible components.
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Authors who are presenting talks have a * after their name.
