Authors: Alexander E. Black, Christoph Hertrich, Stefan Kober, Georg Loho
Organizations: Department of Mathematics, Bowdoin College · Department Liberal Arts and Social Sciences, University of Technology Nuremberg · Department of Mathematics, London School of Economics and Political Science · Institute of Mathematics, Freie Universität Berlin
The extension complexity xc(P) of a polytope P is the minimum number of facets of a polytope that projects onto it. Motivated by the complexity of neural networks, Hertrich and Loho introduced the virtual extension complexity vxc(P) of a polytope P, which is the minimum of xc(Q)+xc(R) among all polytopes Q and R such that P+Q=R. We show the following results pertaining to virtual extension complexity. First, we resolve the core open problem on the topic by showing the virtual extension complexity can be exponentially smaller than extension complexity. Second, we show there are matroid base polytopes with exponential virtual extension complexity by adapting a semi-algebraic counting argument by Hrubeš that extends the counting arguments of Rothvoss. Finally, we show that the maximum virtual extension complexity of a polygon with n vertices is Θ(n). This resolves an analogue of a question on extension complexity of Fiorini, Rothvoss, and Tiwary in 2011 in the case of virtual extension complexity.
Figures & tables
Figure 1. Geometric interpretation of the formula in Proposition 3.4 . A feasible vector u yields q(u):=CQu+cQ∈Q . The dual certificate t , together with the normal d , certifies a valid halfspace for R that is violated by x+q(u) . Hence x∈/P .
Combinatorial optimization finds the best feasible choices among discrete alternatives in routing, scheduling, graph problems, and resource allocation.