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Localized Sliced Inverse Regression
Qiang Wu · Sayan Mukherjee · Feng Liang

Wed Dec 10 07:30 PM -- 12:00 AM (PST) @

We developed localized sliced inverse regression for supervised dimension reduction. It has the advantages of preventing degeneracy, increasing estimation accuracy, and automatic subclass discovery in classification problems. A semisupervised version is proposed for the use of unlabeled data. The utility is illustrated on simulated as well as real data sets.

Author Information

Qiang Wu (Department of Computer Science and Engineering)
Sayan Mukherjee (Duke University)
Feng Liang (University of Illinois at Urbana-Champaign)

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