Bilateral random projections

Publication Type:
Conference Proceeding
Citation:
IEEE International Symposium on Information Theory - Proceedings, 2012, pp. 1286 - 1290
Issue Date:
2012-10-22
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2012004233OK.pdf237.31 kB
Adobe PDF
Low-rank structure have been profoundly studied in data mining and machine learning. In this paper, we show a dense matrix X's low-rank approximation can be rapidly built from its left and right random projections Y 1 = XA 1 and Y 2 = X T A 2, or bilateral random projection (BRP). We then show power scheme can further improve the precision. The deterministic, average and deviation bounds of the proposed method and its power scheme modification are proved theoretically. The effectiveness and the efficiency of BRP based low-rank approximation is empirically verified on both artificial and real datasets. © 2012 IEEE.
Please use this identifier to cite or link to this item: