16 research outputs found
Groups of diffeomorphisms and geometric loops of manifolds over ultra-normed fields
The article is devoted to the investigation of groups of diffeomorphisms and
loops of manifolds over ultra-metric fields of zero and positive
characteristics. Different types of topologies are considered on groups of
loops and diffeomorphisms relative to which they are generalized Lie groups or
topological groups. Among such topologies pairwise incomparable are found as
well. Topological perfectness of the diffeomorphism group relative to certain
topologies is studied. There are proved theorems about projective limit
decompositions of these groups and their compactifications for compact
manifolds. Moreover, an existence of one-parameter local subgroups of
diffeomorphism groups is investigated.Comment: Some corrections excluding misprints in the article were mad
The Riesz–Kantorovich formula for lexicographically ordered spaces
Analysis and Stochastic
Fast, Linear Time Hierarchical Clustering using the Baire Metric
The Baire metric induces an ultrametric on a dataset and is of linear
computational complexity, contrasted with the standard quadratic time
agglomerative hierarchical clustering algorithm. In this work we evaluate
empirically this new approach to hierarchical clustering. We compare
hierarchical clustering based on the Baire metric with (i) agglomerative
hierarchical clustering, in terms of algorithm properties; (ii) generalized
ultrametrics, in terms of definition; and (iii) fast clustering through k-means
partititioning, in terms of quality of results. For the latter, we carry out an
in depth astronomical study. We apply the Baire distance to spectrometric and
photometric redshifts from the Sloan Digital Sky Survey using, in this work,
about half a million astronomical objects. We want to know how well the (more
costly to determine) spectrometric redshifts can predict the (more easily
obtained) photometric redshifts, i.e. we seek to regress the spectrometric on
the photometric redshifts, and we use clusterwise regression for this.Comment: 27 pages, 6 tables, 10 figure