Efficient Dimensionality Reduction for Canonical Correlation Analysis
نویسندگان
چکیده
منابع مشابه
Efficient Dimensionality Reduction for Canonical Correlation Analysis
We present a fast algorithm for approximate canonical correlation analysis (CCA). Given a pair of tall-and-thin matrices, the proposed algorithm first employs a randomized dimensionality reduction transform to reduce the size of the input matrices, and then applies any CCA algorithm to the new pair of matrices. The algorithm computes an approximate CCA to the original pair of matrices with prov...
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ژورنال
عنوان ژورنال: SIAM Journal on Scientific Computing
سال: 2014
ISSN: 1064-8275,1095-7197
DOI: 10.1137/130919222