New Post: How to hook up to the a native provider
Hi Candy, I was able to build OpenBlas with the full LAPACK library. I'll start working on an OpenBlas provider in a couple weeks. Regards, Marcus
View ArticleNew Post: SVD failes to converge
I think i figured what was the problem; turns out I had a couple of NaN values in my matrix which caused the procedure to fail.
View ArticleNew Post: Cut cols and rows (or factor the matrix)
Hi all, I am relevantly new in c# and not a profi (however, I hope to become a such once..), so please do not punish for stupid questions now. I made a singular value decomposition of sparse matrix...
View ArticleNew Post: Cut cols and rows (or factor the matrix)
Basically I do this:https://inst.eecs.berkeley.edu/~ee127a/book/login/exa_low_rank_4by5.htmlA rank-K approximation is given by zeroing out the smallest singular value.
View ArticleNew Post: Cut cols and rows (or factor the matrix)
Ok, I found that answer for question 2 is very simple: var svd = matrix.Svd(true); var matrix_UK = svd.U().SubMatrix(0, svd.W().RowCount, 0, K); var matrix_SKK = svd.W().SubMatrix(0, K, 0, K); var...
View ArticleNew Post: denseSvd returns defferent results each time
Hi I have a denseSvd from which I take the VT matrix as follows: DenseSvd denseSvd = new DenseSvd(X, true); Matrix<double> R = denseSvd.VT(); when I run my program twice on the same values I get...
View ArticleNew Post: denseSvd returns defferent results each time
Hi, Could you post your matrix and the values of VectorS? If there are any duplicate singular values, then R is not unique. If this is the problem, then our SVD implementation isn't stable (though it...
View ArticleNew Post: EigenValue Decomposition - method failing
Native EVD is now up at https://github.com/mathnet/mathnet-numerics-native along with the updated native libraries.
View ArticleNew Post: Cut cols and rows (or factor the matrix)
Hi Alex, I think your solution (#2) is the only one possible given the current SVD implementation. It would be possible to extend the SVD code to handle low rank approximation (it might be better to...
View ArticleNew Post: denseSvd returns defferent results each time
Hi Marcus First of all - thank you very much for taking the time replying to my message. :) here are links to Matrix X which is the input to the SVD. I think it is important to mention that X is also...
View ArticleNew Post: Cut cols and rows (or factor the matrix)
Hi cuda, Thank you for a quick answer! It can be useful for recommender system algorithms. Such algorithms deal with initialization of input matices (which are products of SVD) having huge data array...
View ArticleNew Post: Cut cols and rows (or factor the matrix)
The way SVD is currently set up, during decomposition you will have your original matrix, a copy of the original matrix, a mxm matrix, a nxn matrix, and a min(n, m) vector in memory at one time. So in...
View ArticleNew Post: Cut cols and rows (or factor the matrix)
cuda wrote: That really doesn't matter much since a 500Kx500K dense matrix would take up about 2TB of memory and way above the 2GB maximum object size. We'd have introduce a different storage scheme to...
View ArticleNew Post: Cut cols and rows (or factor the matrix)
AlexKMN wrote: However, I do not know if this is possible at all to make SVD with approximation "built in" without a need to keep 4 500Kx500K in the memory during actual decomposition. I mean that...
View ArticleNew Post: Cut cols and rows (or factor the matrix)
Ok. I go to proposals on GitHub now:) Thank you for you time!
View ArticleNew Post: denseSvd returns defferent results each time
For both matrices, I get the same values for VT no matter how many times I run SVD: -0.326068 0.276482 0.267086 0.190362 0.651066 0.534582 -0.651499 0.504864 -0.0477582 0.306449 -0.391004 -0.267555...
View ArticleNew Post: denseSvd returns defferent results each time
Hi Marcus Here is a code snippet which I've tested and yields different results: private void testFunction() { _denseSvd = new DenseSvd(_L, true); Matrix<double> U = _denseSvd.U(); DenseMatrix X...
View ArticleNew Post: denseSvd returns defferent results each time
Hi Guy, Sorry, every time I run it I get the same answer:X[0,0] : -0.00785276266443448 R: 0 0.628428409244284 0.331639665434677 0.0541319100191873 0.512793332729552 0.478754217726453 0...
View ArticleNew Post: denseSvd returns defferent results each time
and what CPU and operating system are you running this on? and are you using managed or native SVD?
View ArticleNew Post: denseSvd returns defferent results each time
Hi Marcus _L matrix is always the same and never changes. I'm running it intel core i7 - 3610qm Windows 7 premium it's a laptop (if it makes any difference) i've installed Mathnet.numerics through...
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