A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
This paper develops new semidefinite programming (SDP) relaxation techniques for two classes of mixed binary quadratically constrained quadratic programs (MBQCQP) and analyzes their approximation performance. The first class of problem finds two minimum norm vectors in N-dimensional real or complex Euclidean space, such that M out of 2M concave quadratic functions are satisfied. By employing a special randomized rounding procedure, we show that the ratio between the norm of the optimal solutionarXiv:1403.3998v1 fatcat:zuiodtvlgjhkrp6za5iq435wc4