I am trying to do a quadratic programming. I have an affinity matrix A, and I have to maximize certain function x'Ax. This is basically related to feature matching i.e matching points to labels
This is basically related to establish a connection between dominant sets in a weighted graph and local maximizers of the quadratic function
$maximize(f({x} = x^{T}A{x})$
subject to
$x \epsilon\Delta, \Delta:\sum_{j}x_j=1$
To solve this problem I found a method called replicator equation given by Pavan and Pelillo IEEE PAMI 2007
Once an initialization x(1) is given, the discrete replicator equation can be used to obtain a local solution $x^{*}$
$x_i(t+1) = x_i(t+1) \frac{(Ax(t))_i}{x(t)^TAx(t)}$
I get the right results when I use the replicator equation. However, when I try to solve it using matlab's quadprog function like this
X=quadprog(-A,[],[],[],Aeq,Beq,s);
I don't get the right values. Suppose I want to match 7 points with 7 labels, I define my affinity matrix and then use the above. However, using replicator equation I get the right results. But using just quadprog doesn't give me the right results. Any suggestions?