6 citations · 22 across the 16 of their papers we have counts for
17 papers
Computing expected moments of the Rényi parking problem on the circle
Markus Hegland, Conrad J. Burden, Zbigniew Stachurski
A highly accurate and efficient method to compute the expected values of the count, sum, and squared norm of the sum of the centre vectors of a random maximal sized collection of n…
A Note on Error Bounds for Pseudo Skeleton Approximations of Matrices
Frank de Hoog, Markus Hegland
Due to their importance in both data analysis and numerical algorithms, low rank approximations have recently been widely studied. They enable the handling of very large matrices.…
Low rank approximation of positive semi-definite symmetric matrices using Gaussian elimination and volume sampling
Markus Hegland, Frank deHoog
Positive semi-definite matrices commonly occur as normal matrices of least squares problems in statistics or as kernel matrices in machine learning and approximation theory. They a…
Stratified Space Learning: Reconstructing Embedded Graphs
Yossi Bokor, Daniel Grixti-Cheng, Markus Hegland +2
Many data-rich industries are interested in the efficient discovery and modelling of structures underlying large data sets, as it allows for the fast triage and dimension reduction…
Self-referential Functions
Michael Barnsley, Markus Hegland, Peter Massopust
We introduce the concept of fractels for functions and discuss their analytic and algebraic properties. We also consider the representation of polynomials and analytic functions us…
Conjugacies provided by fractal transformations I : Conjugate measures, Hilbert spaces, orthogonal expansions, and flows, on self-referential spaces
Christoph Bandt, Michael Barnsley, Markus Hegland +1
Theorems and explicit examples are used to show how transformations between self-similar sets (general sense) may be continuous almost everywhere with respect to stationary measure…