It is possible because PageRank was a form of eigenvalue and that is why MapReduce introduced. But there seems problems in actual implementation, such as every slave computer have to maintain a copy of the matrix? ...
How expensive is it to compute the eigenvalues of a matrix? What is the complexity of the best algorithms? How long might it take in practice if I have a 1000x1000 matrix? I assume it helps if the matrix is sparse? Are there any cases where the eigenvalue computation would not terminate? In R, I can compute the eigenvalues as in t...
Hello! I would like to implement Singular Value Decomposition (SVD) in PHP. I know that there are several external libraries which could do this for me. But I have two questions concerning PHP, though: 1) Do you think it's possible and/or reasonable to code the SVD in PHP? 2) If (1) is yes: Can you help me to code it in PHP? I've alrea...
Does any know what is the algorithm used for eigenvalues and eigenvectors computation in Intel Math Kernel library? From the link I can find is that it seems to use pdsyev algorithm, which uses QR algorithm, that would deteriorate in the face of large matrix. If this were true, then the mkl isn't a suitable library for computing large ...
I have an unsorted vector of eigenvalues and a related matrix of eigenvectors. I'd like to sort the columns of the matrix with respect to the sorted set of eigenvalues. (e.g., if eigenvalue[3] moves to eigenvalue[2], I want column 3 of the eigenvector matrix to move over to column 2.) I know I can sort the eigenvalues in O(N log N) via ...
I want to compute a diffusion kernel, which involves taking exp(b*A) where A is a large matrix. In order to play with values of b, I'd like to diagonalize A (so that exp(A) runs quickly). My matrix is about 25k x 25k, but is very sparse - only about 60k values are non-zero. Matlab's "eigs" function runs of out memory, as does octave's ...
I need to compute the largest eigenvalue of a (sparse) matrix. I implemented the power iteration method, but it is too slow to converge, so I'd like to use a package for it. Does anyone have a recommendation? What is the best C++ eigenvalue computation package? Preferably one that is small and easy to compile. ...
I tried to find the eigenvalues of a matrix multiplied by its transpose but I couldn't do it using numpy. testmatrix = numpy.array([[1,2],[3,4],[5,6],[7,8]]) prod = testmatrix * testmatrix.T print eig(prod) I expected to get the following result for the product: 5 11 17 23 11 25 39 53 17 39 61 83 23 53 ...
Hi all, which java package do you recommend for computing eigenvectors/eigenvalues? I know about JMathTools and JAMA; do you have some pro/cons for these packages? Other suggestions? ...
I am trying to find a program in C code that will allow me to compute a eigenvalue (spectral) decomposition for a square matrix. I am specifically trying to find code where the highest eigenvalue (and therefore its associated eigenvalue) are located int the first column. The reason I need the output to be in this order is because I am t...
In MATLAB when I run the command [V,D] = eig(a) for a symmetric matrix the largest eigenvalue (and its associated vector) is located in last column. However, when I run it with a non-symmetric matrix however the largest eigenvalue is in the first column. I am trying to calculate eigenvector centrality which requires that I take the compu...
Possible Duplicate: Eigenvector (Spectral) Decomposition I am trying to find a program in C code that will allow me to compute a eigenvalue (spectral) decomposition for a square matrix. I am specifically trying to find code where the highest eigenvalue (and therefore its associated eigenvalue) are located int the first column....
I'm currently in the process of writing a function to find an "exact" bounding-sphere for a set of points in 3D space. I think I have a decent understanding of the process so far, but I've gotten stuck. Here's what I'm working with: A) Points in 3D space B) 3x3 covariance matrix stored in a 4x4 matrix class (referenced by cells m0,m1,m2...