Dimensionality reduction is standard practice for filtering noise and identifying relevant
features in large-scale data analyses. In biology, single-cell genomics studies typically begin …

The classification loss functions used in deep neural network classifiers can be grouped into
two categories based on maximizing the margin in either Euclidean or angular spaces …

The classification loss functions used in deep neural network classifiers can be split into two
categories based on maximizing the margin in either Euclidean or angular spaces …

Bounding the Size of an Almost-Equidistant Set in Euclidean Space Page 1 Combinatorics,
Probability and Computing (2019) 28, 280–286. c Cambridge University Press 2018 doi:10.1017/S0963548318000287 …

In single-cell genomics, we can simultaneously assay hundreds of thousands of cells, their
molecular contents, and how they respond to perturbation, from genetic knockouts to …

On almost-equidistant sets - ScienceDirect Skip to main contentSkip to article Elsevier logo
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Sažetak This paper introduces shape boundary regions in descriptive proximity forms of CW
(Closure-finite Weak) spaces as a source of amiable fixed subsets as well as almost amiable …

A set in $\mathbb R^ d $ is called almost-equidistant if for any three distinct points in the set,
some two are at unit distance apart. First, we give a short proof of the result of Bezdek and …

Supplementary Figure 1: Principal Components of Equidistant Points. a) First and second
principal components shown for varying numbers of equidistant points, ie the In identity …

Basic concept of an equidistant set to a manifold reveals a bundle of problems connected to
intrinsic geometric properties of the resulting geometric figure. Interesting problems of …