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01 Nov 2013 Merge sorted arrays Given two already sorted arrays, the function combines them in an unique sorted array Author: Bruno Luong

Hi Bruno, thanks for a useful tool. It comes in handy for efficiently summing sparse tensors together. On my system there appears to be a bug when one of the two arrays is empty (see example case below). Is this a compilation problem on my system or a bug in the algorithm? Thanks!

>> [C idx]=mergesa([],[1 1 1; 3 1 1],'rows')

C =

1 1 1
3 1 1

idx =


20 Dec 2012 M-file dependency consolidator Will take a given m-file, or directory of such files, and consolidate any dependent m/mex files Author: Jit

Friend, I owe you a drink. At the very least.

23 Aug 2012 LBFGSB (L-BFGS-B) mex wrapper Mex wrapper for lbfgsb v3.0 fortan library. L-bfgs-b solves box-constrained optimization. Author: Stephen Becker

Couldn't get it to run despite trying all options including the f2c. Compiles and crashes when I try to run an example. I'm running OS X 10.6, Matlab 2011a, 64 bit, with gcc 4.6.2 (prerelease) and Blas 10.2.6. Could it be that my compiler is too new? Matlab documentation says I need an older gcc, 3.2, and older gfortran, 4.3.x.

22 Aug 2012 MTRON MTRON is a Matlab wrapper for the Fortran software TRON (a large scale trust region Newton method). Author: Christoph Ortner

I used Stephen's command verbatim to compile on 64 bit OS X (Snow Leopard). mex complained about "assignment from incompatible pointer type" in the copy_H function of mtron.c. So in addition to Son Le's modifications to mtron.c, I also had to change

in mtron.c, line 108: mwIndex *irt, *jct;

Now it seems to work great. (Bizarrely, the code occasionally worked before the line 108 modification, but was very slow.)

14 Apr 2011 Multiple matrix multiplications, with array expansion enabled Multiplying matrices, vectors, or scalars contained in two N-D arrays, with array expansion enabled. Author: Paolo de Leva

Incredible! I have to do a series of structured matrix-vector multiplications where the matrices have identical structure. There was no way to do this with built-in matlab functionality, outside of using a FOR loop. A MULTIPROD-based implementation turned out to be 100-1000 times faster on problems of practical size!

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