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SUMMARY:Ming Hsieh Department of Electrical Engineering Seminar
DESCRIPTION:Restricted Isometry Property of Gaussian Random Projection for Low-Dimensional Subspaces\n
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Professor Yuantao Gu\n
Tsinghua University\n
Beijing, China\n
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Abstract: Dimensionality reduction is in demand to reduce the complexity of solving large-scale problems with data lying in latent low-dimensional structures in machine learning and computer version. Motivated by such need, in this talk I will introduce the Restricted Isometry Property (RIP) of Gaussian random projections for low-dimensional subspaces in R^N, and prove that the projection Frobenius norm distance between any two subspaces spanned by the projected data in R^n for n
DTSTART:20180220T100000
LOCATION:EEB 248
URL;VALUE=URI:
DTEND:20180220T230000
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