Algorithms for Tverberg's theorem via centerpoint theorems
classification
💻 cs.CG
math.CO
keywords
algorithmsconvexitygraphscenterpointeuclideangeodeticnumberobtain
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We obtain algorithms for computing Tverberg partitions based on centerpoint approximations. This applies to a wide range of convexity spaces, from the classic Euclidean setting to geodetic convexity in graphs. In the Euclidean setting, we present probabilistic algorithms which are weakly polynomial in the number of points and the dimension. For geodetic convexity in graphs, we obtain deterministic algorithms for cactus graphs and show that the general problem of finding the Radon number is NP-hard.
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Stochastic Tverberg theorems and their applications in multi-class logistic regression, data separability, and centerpoints of data
Stochastic Tverberg theorems give probability bounds for common convex hull intersections of random classes, yielding bounds on MLE existence in multinomial logistic regression.
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