I want to solve a group Lasso minimization problem with optimization variable matrix \mathbf{W} \in \mathcal{C}^{N\times M} when there is a square of norm expression in the objective function but according to the DCP rules I can not use the square function of a norm operation (it gives a DCP error). How do we handle this problem in CVX since there are lots of optimization problem that they deal with square of norm?
Here is my objective function :
minimize ||\mathbf{HW-I_M}||_F^2+\sum_{i=1}^N ||\mathbf{w}_i||_2,
where $\mathbf{w}_i$s are the rows of \mathbf{W} and \mathbf{H} \in \mathcal{C}^{M\times N}.
currently I wrote the problem in Matlab as follows but I can not square the first norm expression.
%
cvx_begin
i=N;
j=M;
variable w(i,j) complex;
minimize( norm(H*w-I,‘fro’) + \lambda .*sum( norms(w,2,2) ) );
cvx_end
%