47 search results - page 2 / 10 » Adaptive Sampling and Fast Low-Rank Matrix Approximation |
TKDE
2012
11 years 7 months ago
2012
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
SIAMMAX
2010
12 years 11 months ago
2010
The problem of completing a low-rank matrix from a subset of its entries is often encountered in the analysis of incomplete data sets exhibiting an underlying factor model with app...
STOC
2009
ACM
14 years 5 months ago
2009
ACM
The low-rank matrix approximation problem involves finding of a rank k version of a m ? n matrix AAA, labeled AAAk, such that AAAk is as "close" as possible to the best ...
APPROX
2006
Springer
13 years 8 months ago
2006
Springer
We describe a simple random-sampling based procedure for producing sparse matrix approximations. Our procedure and analysis are extremely simple: the analysis uses nothing more th...
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
Reducing the number of secondary data used to estimate the Clutter Covariance Matrix (CCM) for Space Time Adaptive Processing (STAP) techniques is still an active research topic. ...