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What and Who

PhD Defense Karl Bringmann

Karl Bringmann
MMCI
Promotionskolloquium
AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI  
Public Audience
English

Date, Time and Location

Wednesday, 17 December 2014
12:30
60 Minutes
E1 4
024
Saarbrücken

Abstract

In the first part of this thesis, we study the fundamental problem of
sampling from a discrete probability distribution. Specifically, given
non-negative numbers p_1,...,p_n the task is to draw i with probability
proportional to p_i. We extend the classic solution to this problem,
Walker's alias method, in various directions: We improve its space
requirements, we solve the special case of sorted input, we study
sampling natural distributions on a bounded precision machine, and as an
application we speed up sampling a model from physics.

The second part of this thesis belongs to the area of computational
geometry and deals with algorithms for the Fréchet distance, which is a
popular measure of similarity of two curves and can be computed in
quadratic time (ignoring logarithmic factors). We provide the first
conditional lower bound for this problem: No polynomial factor
improvement over the quadratic running time is possible unless the
Strong Exponential Time Hypothesis fails. We also present an improved
approximation algorithm for realistic input curves.

Contact

Christina Fries
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Christina Fries, 12/08/2014 14:05 -- Created document.