comparison toolboxes/distance_learning/mlr/loss/lossHingeDODMKL.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function Xi = lossHingeDODMKL(W, Psi, M, gradient)
+%
+%   Xi = lossHingeDODMKL(W, Psi, M, gradient)
+%   
+%   W:          m*m*d matrix of diagonal metrics
+%   Psi:        m*m*d feature matrix
+%   M:          the desired margin
+%   gradient:   if 0, returns the loss value
+%               if 1, returns the gradient of the loss WRT W
+
+    m = size(W,1);
+
+    Xi = max(0, M - sum(sum(sum(W .* Psi))));
+
+    if gradient & Xi > 0
+        Xi = -Psi;
+    end
+end