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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?

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