Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 171 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 28 tok/s Pro
GPT-5 High 31 tok/s Pro
GPT-4o 92 tok/s Pro
Kimi K2 202 tok/s Pro
GPT OSS 120B 435 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Optimal stochastic planarization (1004.1666v2)

Published 10 Apr 2010 in cs.CG, cs.DM, cs.DS, and math.MG

Abstract: It has been shown by Indyk and Sidiropoulos [IS07] 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 [BLS09]. 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 [BLS09] 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-g graphs, to corresponding ones on planar graphs, with a O(log g) loss factor in the approximation guarantee.

Citations (10)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.