BIRSVD - Bi-Iterative Regularized Singular Value Decomposition
DESCRIPTION
BIRSVD is a MATLAB based software to compute the regularized low rank
approximation of large weighted data sets. For regularization BIRSVD use
a priori information that the low rank approximants are smooth. BIRSVD is
an appropriate choice whenever such a priori information is available.
BIRSVD is fast, i.e., the number of flops per iteration is of the order
of the number of data points, and memory usage is negligible compared with
the input data storage.
Details about the method and experimental results are available in the
manuscript
If you prepare publications based on programs using this software,
please cite this paper (or its published version, once published).
SOFTWARE DOWNLOAD
The software is available for download as a
tarball. The software is compatible with MATLAB version 7 or higher.
No toolbox is required.
The software contains MATLAB source code of the BIRSVD algorithm as
well as drivers for demonstration. Two test data sets are also available
within this software package.
USAGE
Unpack the tarball, add the location of BIRSVD in the MATLAB path,
and it is ready to use.
Calling Sequence
[U, S, V] = BIRSVD(A, W, rnk, param_in)
returns component of a low rank (rnk) approximation [U, S, V] of an
weighted data set A accompanied with a weight matrix W. The
solution is regularized using a priori information that the
approximants (i.e. columns of U and V) are smooth.
Within MATLAB use:
">> help BIRSVD"
for further details on usage.
For generating default parameters, call BIRSVD without any input argument.
AUTHOR / BUG REPORT
This software is written by Saptarshi Das and Arnold Neumaier,
without any guarantee of perfomance (though it is likely to perform
very well). For queries or bug reports, contact
arnold.neumaier@univie.ac.at.
Global (and Local) Optimization
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my home page
(http://arnold-neumaier.at)
Arnold Neumaier (Arnold.Neumaier@univie.ac.at)