Concave Mixed-Integer Quadratic Programming is the problem of minimizing a concave quadratic polynomial over the mixed-integer points in a polyhedral region. In this work we describe two algorithms that find an -approximate solution to a Concave Mixed-Integer Quadratic Programming problem. The running time of the proposed algorithms is polynomial in the size of the problem and in 1/ , provided ...

Machine learning (ML) has been recently introduced to solving optimization problems, especially for combinatorial (CO) tasks. In this paper, we survey the trend of leveraging ML solve mixed-integer programming problem (MIP). Theoretically, MIP is an NP-hard problem, and most CO problems can be formulated as MIP. Like other human-designed heuristic algorithms rely on good initial solutions cost ...