[mlpack-svn] [MLPACK] #160: Sparse matrix factorizations (QR, LU, SVD, etc.)

[MLPACK Trac]

#160: Sparse matrix factorizations (QR, LU, SVD, etc.)
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  Reporter:  rcurtin                                 |        Owner:            
      Type:  enhancement                             |       Status:  new       
  Priority:  major                                   |    Milestone:  MLPACK 1.0
 Component:  MLPACK                                  |   Resolution:            
  Keywords:  sparse matrix factorizations qr lu svd  |     Blocking:  110       
Blocked By:                                          |  
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Comment (by jcline3):

 After looking around a bit before going to sleep, I found 8 possibilities,
 but I need to look over the details a bit closer. I'm making a rather
 detailed list of features and what's missing, and possible issues for each
 one.

 Is there anything aside from QR, LU, and SVD that we need? A few of the
 libraries I have found have some additional, possibly useful, algorithms.
 If it is just these three things that we care about, it may be reasonable
 to implement them ourselves. It's only a few hundred lines of code for all
 three with dense matrices, so it's probably not much more for sparse.
 (Admittedly, there are some slight issues that we would need to pay
 attention to, numerical stability, overflow and underflow...)

-- 
Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/160#comment:1>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed by the FASTLAB at Georgia Tech under Dr. Alex Gray.