21 search results - page 1 / 5 » Heteroscedastic Low-Rank Matrix Approximation by the Wiberg ... |
TSP
2008
13 years 4 months ago
2008
Abstract--Low-rank matrix approximation has applications in many fields, such as 2D filter design and 3D reconstruction from an image sequence. In this paper, one issue with low-ra...
TKDE
2012
11 years 6 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...
SIAMSC
2011
12 years 11 months ago
2011
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
We prove that for any real-valued matrix X ∈ Rm×n , and positive integers r k, there is a subset of r columns of X such that projecting X onto their span gives a r+1 r−k+1 -a...
SDM
2011
SIAM
12 years 7 months ago
2011
SIAM
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...