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Activity Number:
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508
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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| Abstract - #308879 |
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Title:
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An Extension of Fisher's Discriminant Analysis for Stochastic Processes
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Author(s):
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Hyejin Shin*+
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Companies:
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Auburn University
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Address:
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221 Parker Hall, Auburn, AL, 36849,
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Keywords:
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Fisher's discriminant analysis ; reproducing kernel Hilbert space ; stochastic processes
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Abstract:
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Modern data collection methods are now frequently returning observations that should be viewed as the result of digitized recording or sampling from stochastic processes rather than vectors of finite length. Our focus in this talk is on discrimination and classification in the infinite dimensional setting. Specially, we have developed a theoretical framework for Fisher's linear discriminant analysis of sample paths from stochastic processes through use of the Loeve-Parzen isomorphism that connects a second order process to the reproducing kernel Hilbert space generated by its covariance kernel. This approach provides a seamless transition between finite and infinite dimensional settings and lends itself well to computation via smoothing and regularization.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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