Abstract
We generalize the reduction mechanism between linear programming problems from [1] in two ways (1) relaxing the requirement of affineness, and (2) extending to fractional optimization problems. As applications we provide several new LP-hardness and SDPhardness results, e.g., for the SparsestCut problem, the BalancedSeparator problem, the MaxCut problem and the Matching problem on 3-regular graphs. We also provide a new, very strong Lasserre integrality gap for the IndependentSet problem, which is strictly greater than the best known LP approximation, showing that the Lasserre hierarchy does not always provide the tightest SDP relaxation.
Cite
CITATION STYLE
Braun, G., Pokutta, S., & Roy, A. (2016). Strong reductions for extended formulations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9682, pp. 350–361). Springer Verlag. https://doi.org/10.1007/978-3-319-33461-5_29
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
