【摘 要】
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Feature extraction corresponds to reduced rank modeling which has been widespread real-world applications.This talk investigates non-asymptotic performance of rank penalized estimators.The constructio
【机 构】
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Department of Statistics, Florida State University 117 N.Woodward Ave.Tallahassee, FL 32306
【出 处】
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The Third IMS-China International Conference on Statistics a
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Feature extraction corresponds to reduced rank modeling which has been widespread real-world applications.This talk investigates non-asymptotic performance of rank penalized estimators.The construction of new features via a re duced set of input variables is much more convenient and interpretable in highdimensional applications.A novel selective reduced rank regression is proposed for joint feature extraction and selection.Applications in cognitive neuroscience and macroeconometrics are presented.
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