Mercurial > hg > camir-aes2014
annotate toolboxes/distance_learning/mlr/regularize/regularizeMKLDOD.m @ 0:e9a9cd732c1e tip
first hg version after svn
| author | wolffd |
|---|---|
| date | Tue, 10 Feb 2015 15:05:51 +0000 |
| parents | |
| children |
| rev | line source |
|---|---|
| wolffd@0 | 1 function r = regularizeMKLDOD(W, X, gradient) |
| wolffd@0 | 2 % |
| wolffd@0 | 3 % r = regularizeMKLDOD(W, X, gradient) |
| wolffd@0 | 4 % |
| wolffd@0 | 5 % |
| wolffd@0 | 6 |
| wolffd@0 | 7 [d,n,m] = size(X); |
| wolffd@0 | 8 |
| wolffd@0 | 9 if gradient |
| wolffd@0 | 10 r = zeros(m,m,d); |
| wolffd@0 | 11 for i = 1:m |
| wolffd@0 | 12 r(i,i,:) = diag(X(:,:,i)); |
| wolffd@0 | 13 for j = (i+1):m |
| wolffd@0 | 14 r(i,j,:) = diag(X(:,:,i)) + diag(X(:,:,j)); |
| wolffd@0 | 15 end |
| wolffd@0 | 16 end |
| wolffd@0 | 17 else |
| wolffd@0 | 18 r = 0; |
| wolffd@0 | 19 for i = 1:m |
| wolffd@0 | 20 r = r + squeeze(W(i,i,:))' * diag(X(:,:,i)); |
| wolffd@0 | 21 for j = (i+1):m |
| wolffd@0 | 22 r = r + squeeze(W(i,j,:))' * (diag(X(:,:,i)) + diag(X(:,:,j))); |
| wolffd@0 | 23 end |
| wolffd@0 | 24 end |
| wolffd@0 | 25 end |
| wolffd@0 | 26 end |