I understand that we can approximate solutions to Integer Quadratic Programming optimization problems containing just a positive semi definite matrix, as outlined here (i.e. the Q matrix): https://learning-modules.mit.edu/service/materials/groups/116310/files/c33fb8f4-417a-46b2-9772-7c44b8912290/link?errorRedirect=/materials/index.html
However, I'm wondering if the Semi Definite Programming relaxation method extends to more general Mixed Integer Quadratic Programming problems that also contain a vector scalar product in the objective function, e.g. as described here: http://www.orsj.or.jp/ramp/2014/paper/4-3.pdf
