Generalizing Graph Matching beyond Quadratic Assignment Model

We show that a large family of functions, which we define as Separable Functions, can approximate discrete graphmatching inthecontinuous domain asymptotically byvaryingthe approximation controlling parameters. We also study the properties of global optimality and devise convex/concave-preserving extensions to the widely used Lawler'sQAPform.