Graduiertenkolleg: Methods for Discrete Structures

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Monday Lecture and Colloquium


Monday, January 5, 2015

Freie Universität Berlin
Institut für Informatik
Takustraße 9
14195 Berlin
room 005



Lecture - 14:15

Christian Haase - Freie Universität Berlin


Some facets of marginal polytopes

Abstract:
In this talk, I would like to introduce a class of convex polytopes which appear under different names in different fields of mathematics. For instance, they go by the name of ``marginal polytopes'' in statistics, they are called ``partial constraint satisfaction polytopes'' in combinatorial optimization. They occur as representation polytopes of abelian permutation groups, and they are used in tensor decomposition analysis.

In the general setting, a polytope in the family is specified by a simplicial complex $\Delta$ with vertices labeled by positive integers. If all labels are equal to $2$ (binary case), and if $\Delta$ is a graph, the polytope is a cut polytope.

In spite of their many uses, the facet structure of marginal polytopes remains mysterious --- particularly so in the non-binary case. In joint work with Benjamin Nill and Andreas Paffenholz, we describe a generalization of the cycle inequalities for cut polytopes to non-binary labels together with a polynomial time separation algorithm if the size of the vertex labels is bounded.



Colloquium - 16:00

Heuna Kim - Freie Universität Berlin


Congruence testing for point sets in 4-space.

Abstract:
We give an O(n log n) time algorithm for the exact congruence testing problem for two sets of n points in 4-space. This problem is to decide if two point sets in the 4-dimensional Euclidean space are the same up to rotations and translations. The problem is sensitive to numerical errors, but since congruence testing with error tolerances is known to be NP-hard, we restrict our concern to the exact case and use the Real Random-Access Machine (Real-RAM) model.

For two and three dimensions, there are O(n log n) algorithms due to Manacher (1976) and Atkinson (1987). It has been conjectured that O(n log n) algorithms should exist for any fixed dimension. The best algorithm so far by Brass and Knauer (2000) takes O(n^ceil(d/3) log n) time in d-dimensional space and therefore O(n^2 log n) in 4-space.




Letzte Aktualisierung: 04.01.2015