comparison toolboxes/distance_learning/mlr/regularize/regularizeMKLDOD.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function r = regularizeMKLDOD(W, X, gradient)
+%
+% r = regularizeMKLDOD(W, X, gradient)
+%
+%
+
+    [d,n,m] = size(X);
+
+    if gradient
+        r = zeros(m,m,d);
+        for i = 1:m
+            r(i,i,:) = diag(X(:,:,i));
+            for j = (i+1):m
+                r(i,j,:) = diag(X(:,:,i)) + diag(X(:,:,j));
+            end
+        end
+    else
+        r = 0;
+        for i = 1:m
+            r = r + squeeze(W(i,i,:))' * diag(X(:,:,i));
+            for j = (i+1):m
+                r = r + squeeze(W(i,j,:))' * (diag(X(:,:,i)) + diag(X(:,:,j)));
+            end
+        end
+    end
+end