46 citations · 165 across the 16 of their papers we have counts for
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stat.ML2016★ 6 cited
Kernel functions based on triplet comparisons
Matthäus Kleindessner, Ulrike von Luxburg
Given only information in the form of similarity triplets "Object A is more similar to object B than to object C" about a data set, we propose two ways of defining a kernel functio…
stat.ML2016★ 9 cited
Lens depth function and k-relative neighborhood graph: versatile tools for ordinal data analysis
Matthäus Kleindessner, Ulrike von Luxburg
In recent years it has become popular to study machine learning problems in a setting of ordinal distance information rather than numerical distance measurements. By ordinal distan…