Title :
Optimal Stochastic Planarization
Author :
Sidiropoulos, Anastasios
Author_Institution :
Toyota Technol. Inst. at Chicago, Chicago, IL, USA
Abstract :
It has been shown by Indyk and Sidiropoulos that any graph of genus g > 0 can be stochastically embedded into a distribution over planar graphs with distortion 2O(g). This bound was later improved to O(g2) by Borradaile, Lee and Sidiropoulos. We give an embedding with distortion O(log g), which is asymptotically optimal. Apart from the improved distortion, another advantage of our embedding is that it can be computed in polynomial time. In contrast, the algorithm of requires solving an NP-hard problem. Our result implies in particular a reduction for a large class of geometric optimization problems from instances on genus-p graphs, to corresponding ones on planar graphs, with a O(log g) loss factor in the approximation guarantee.
Keywords :
computational complexity; graph theory; optimisation; stochastic processes; NP-hard problem; approximation guarantee; asymptotically optimal; genus-p graphs; geometric optimization problems; optimal stochastic planarization; planar graphs; polynomial time; Extraterrestrial measurements; Generators; Minimization; Optimization; Partitioning algorithms; Polynomials; embeddings; genus; planar graphs;
Conference_Titel :
Foundations of Computer Science (FOCS), 2010 51st Annual IEEE Symposium on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-8525-3
DOI :
10.1109/FOCS.2010.23