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Randomized SVD with single pass over data matrix.

This package includes the codes and experimental data regarding paper:

Wenjian Yu, Yu Gu, Jian Li, Shenghua Liu, and Yaohang Li, Single-Pass PCA of Large High-Dimensional Data, to appear in Proc. IJCAI 2017, pp. 3350-3356. report #1704.07669.

If you used this package, please cite the above paper, or send email to me letting me know. Thank you!

1.This package includes the codes in Matlab for generating the test data, and drawing the figures in the paper, and the codes in C implementing the algorithms tested in the paper.

2.The Matlab programs for generating test matrices.

-PCAtestmatrix.m: generate 5 types of test matrices.

-genLargeMatrix.m: a script generating large matrix stored on hard disk.

-genFeretMatrix.m: generate the 150GB matrix from the FERET database.

(To obtain the FERET database, please follow the instructions on

3.The Matlab programs for the algorithms.

-rSVDbasic.m: the basic randomized algorithm for computing SVD. (Algorithm 1)

-rSVD_exSP.m: the existing single-pass algorithm for randomized SVD. (Algorithm 2)

-rSVDsp.m: the proposed single-pass algorithm for computing SVD. (Algorithm 4)

4.The Matlab programs for drawing figures.

-showSigmaDist.m: a script drawing the singular value distribution (Fig. 2).

-plotfig3.m: draw singular values obtained from the algorithms for two matrices (Fig. 3)

-acc_valid.m: detailed comparison of the obtained singular values (for Fig. 4).

-acc_singvec.m: detailed comparison of the obained singular vectors (for Fig. 5).

-drawFeretSigma: draw the singular value of Feret matrix (Fig. 6a).

-drawEigface.m: draw the four eigenfaces (Fig. 6b).

5.The C program for generating large test data and implementing the algorithms.

Please unpack the tar file rSVDsp-C.tar, and then read the README there. The program has been tested on a Ubuntu Linux machine, with Intel ICC with MKL library.

For comment/question/suggestion, please send email to yu-wj at tsinghua dot edu dot cn (Dr. Wenjian Yu).


randomized SVD with single pass over data matrix





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