I just installed cvxquad and made a first trial. Unfortunately, I get the wrong result, as shown when running the following example code

```
N=10;
M=3;
lambda=rand(N,1);
Pmax=1;
B=rand(M,N);
% Original CVX solution (slow!!!)
cvx_begin
variable p(N,1) nonnegative;
maximize sum_log(1+p.*lambda);
subject to
B*p <= Pmax;
cvx_end
p_origcvx=p;
% CVXQUAD solution (faster, but wrong!!!)
cvx_begin
variable p(N,1) nonnegative;
minimize sum(rel_entr(1,1+p.*lambda));
subject to
B*p <= Pmax;
cvx_end
p_cvxquad=p;
fprintf('Optimal cost, orig CVX=%g\n',sum_log(1+p_origcvx.*lambda));
fprintf('Optimal cost, CVXQUAD=%g = cvx_optval*%g\n',sum_log(1+p_cvxquad.*lambda),N);
```

I use CVX Version 2.1, Build 1127 on Matlab R2018b and downloaded cvxquad today. As it should be, the equality

-sum(rel_entr(1,1+p.*lambda)) = sum_log(1+p.*lambda)

holds numerically, so the cost functions are the same not only in theory but also in practice (even though what goes on under the hood is completely different). I also have my own primal dual custom made algorithm that gives the same result as the original CVX solver, so I trust that one. Is it a bug in cvxquad or did I oversee something obvious?

/Mats