I am trying to understand how to solve convex optimisation problems using solvers such as CVXOPT as I am trying to solve a convex problem and would need to know how to plug in these numbers into the solver. My knowledge of this field is thus very limited.
Most of the quadratic programming problems that is phrased is in the formform minimize $1/2x^TPx + q^Tx $ subject to $Gx \preccurlyeq h, Ax = b$.
However, the problem that I face is when there are more than 2 variables to minimise / maximise. An example is shown here $w^T$, and $\mu$ are vectors and $t$ is a scalar.
This image is taken from the https://ai.stanford.edu/~ang/papers/icml04-apprentice.pdf I am not sure how 2 variables can be minimised / maximised at the same time.