20 citations · 22 across the 15 of their papers we have counts for
4 papers · 1 filter
Union-Free Generic Depth for Non-Standard Data
Hannah Blocher, Georg Schollmeyer
Non-standard data, which fall outside classical statistical data formats, challenge state-of-the-art analysis. Examples of non-standard data include partial orders and mixed catego…
Reciprocal Learning
Julian Rodemann, Christoph Jansen, Georg Schollmeyer
We demonstrate that a wide array of machine learning algorithms are specific instances of one single paradigm: reciprocal learning. These instances range from active learning over…
Statistical Multicriteria Benchmarking via the GSD-Front
Christoph Jansen, Georg Schollmeyer, Julian Rodemann +2
Given the vast number of classifiers that have been (and continue to be) proposed, reliable methods for comparing them are becoming increasingly important. The desire for reliabili…
Data depth functions for non-standard data by use of formal concept analysis
Hannah Blocher, Georg Schollmeyer
In this article we introduce a notion of depth functions for data types that are not given in standard statistical data formats. We focus on data that cannot be represented by one…