This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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81
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #306803 |
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Title:
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The Orthogonal Matching Pursuit Algorithm on Sparse Linear Regression
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Author(s):
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Lie Wang*+ and Tony Cai
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Companies:
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MIT and University of Pennsylvania
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Address:
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, , MA, 02139,
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Keywords:
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Orthogonal matching pursuit ;
variable selection ;
sparse linear regression
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Abstract:
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We consider the orthogonal matching pursuit algorithm on the variable selection of the sparse regression problem. This is a stepwise algorithm. At each step, we select the variable that is best correlated with the current residuals. Sufficient conditions under which the algorithm will select all the correct variables with high probability and the stopping rules are given for both bounded and Gaussian noise cases.
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