I am new to CVX. I might be overlooking the DCP set rules. But I do not manage to run the problem (related to support vector regression–please see the attachment) in CVX.
Updated (to make the software run):
clear variables N = 100; M = 2; w = [1;-1]; % weights x = randn(2,N); % input data e = randn(1,N); % noise y = (w.')*x + e; y = y.'; lambda = 0.9; eps = 0.5; C = 1/lambda; cvx_begin variables a(N) a_hat(N) minimize( norm((sum(a-a_hat))*x, 2) - ((a-a_hat)'*y) + eps * sum(a+a_hat) ) subject to 0 <= a <= C; 0 <= a_hat <= C; sum(a) - sum(a_hat) == 0; cvx_end
Your help will be highly appreciated.
Additional questions: For some reasons, I can’t reply to Mark et al.
Instead of this cost " norm((sum(a-a_hat))*x, 2) ", I would like to implement with summation as given in the last part of eqn. (11.48) in the snapshot. Please suggest.
Thank you so much