Abstract Details
Activity Number:
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108
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Type:
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Invited
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Date/Time:
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Monday, August 5, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #307015 |
Title:
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Two-Way Regularized Logistic Regression with Dynamic Image Regressors
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Author(s):
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T Siva Tian*+ and Jianhua Z. Huang
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Companies:
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University of Houston and Texas A&M University
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Keywords:
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Logistic regression ;
Two-way regularization ;
Classification ;
Spatio-temporal data
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Abstract:
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We propose a novel two-way regularized logistic regression method to classify patients based on the spatio-temporal features presented in the dynamic MEG images. One important characteristic distinguishing the proposed method from existing classification methods is that our method uses a time series of images as predictors. Moreover, we use reduced-rank representation and spatio-temporal regularization to overcome the statistical and computational challenges associated with the high dimensionality of the predictors. A multi-level coordinate descent algorithm is utilized to optimize the log-likelihood function.
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Authors who are presenting talks have a * after their name.
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