An asymptotic model for extreme behavior of certain Markov chains is the ``tail chain''. Generally taking the form of a multiplicative random walk, it is useful in deriving extremal characteristics such as point process limits. We place this model in a more general context, formulated in terms of extreme value theory for transition kernels, and extend it by formalizing the distinction between e...

Classical techniques for analysing multivariate extremes can often be framed in terms of the point process representation of de Haan (1985). Amongst other things, this representation provides a characterisation of the limiting distribution of the normalised componentwise maxima of independent and identically distributed unit Fréchet variables, i.e. the class of multivariate extreme value distri...

Interval-flow networks are a special class of network models that can include minimum-flow requirements on some or all active arcs in a feasible solution. While this extension expresses constraints often encountered in practice, the resulting NP-hard problems are challenging to solve by standard means. This work describes a heuristic that explores adjacent extreme-point solutions to quickly fin...

We study determinantal translation-invariant random point processes on the real line. Under some technical assumptions on the correlation kernel, we prove that the smallest nearest spacings in a large interval have Poisson statistics as the length of the interval goes to infinity. 2000 Math. Subj. Class. 60G55, 60G70.

We generalize to arbitrary bases recent results on the star extreme discrepancy of digitally shifted two-dimensional Hammersley point sets in base 2 by Kritzer, Larcher and Pillichshammer. The key idea is to link our fundamental formula for the discrepancy function of generalized van der Corput sequences to the corresponding quantity for generalized two-dimensional Hammersley point sets. In tha...

We study capacitated network flow problems with demands defined on a countably infinite collection of nodes having finite degree. This class of network flow models includes, for example, all infinite horizon deterministic dynamic programs with finite action sets, because these are equivalent to the problem of finding a shortest path in an infinite directed network. We derive necessary and suffi...

We study capacitated network flow problems with supplies and demands defined on a countably infinite collection of nodes having finite degree. This class of network flow models includes, for example, all infinite horizon deterministic dynamic programs with finite action sets since these are equivalent to the problem of finding a shortest infinite path in an infinite directed network. We derive ...

subject to A X = b and that,X is an extreme point of DX=d, X>O, is developed. The procedure will avoid the investigation of many of the extreme points of DX = d, X > 0 and also alternative optimas of different best extreme points of DX = d, X >_ 0 will not be needed. The algorithm is expected to work very efficiently. Zusammenfassung: In dieser Arbeit "Strong-Cut Enumerative Procedure for Extre...

We present a novel approach for extreme simplification of point set models, in the context of realtime rendering. Point sets are often rendered using simple point primitives, such as oriented discs. However, this requires using many primitives to render even moderately simple shapes. Often, onewishes to render a simplified model using only a few primitives, thus trading accuracy for simplicity....

We investigate geometric features of the unit ball corresponding to the sum of the nuclear norm of a matrix and the l1 norm of its entries — a common penalty function encouraging joint low rank and high sparsity. As a byproduct of this effort, we develop a calculus (or algebra) of faces for general convex functions, yielding a simple and unified approach for deriving inequalities balancing the ...