Here are some small examples of convex objectives (under minimization) one would expect to work.
Objective | CVXPY code | Result | Notes |
---|---|---|---|
xTx | x.T@x | DCP error | print shows minimize x@x, i.e. transpose is dropped |
xTx | x@x | DCP error | |
xTx | cp.sum_squares(x) | transformed into quad_over_lin(x, 1.0) | |
xTQx | x.T@Q@x | transformed into QuadForm(x,Q) | |
y:=x−pxTQy | y=x-p x.T@Q@y | DCP error | |
xTQx−xTQp | x.T@Q@x - x.T@Q@p | first term transformed into QuadForm(x,Q) |
Not everything makes sense to me. I am not sure why x.T@x is not properly recognized, but x.T@Q@x is.