10 citations · 16 across the 2 of their papers we have counts for
2 papers
stat.ML2016★ 10 cited
Learning with Hierarchical Gaussian Kernels
Ingo Steinwart, Philipp Thomann, Nico Schmid
We investigate iterated compositions of weighted sums of Gaussian kernels and provide an interpretation of the construction that shows some similarities with the architectures of d…
stat.ML2015★ 6 cited
Towards an Axiomatic Approach to Hierarchical Clustering of Measures
Philipp Thomann, Ingo Steinwart, Nico Schmid
We propose some axioms for hierarchical clustering of probability measures and investigate their ramifications. The basic idea is to let the user stipulate the clusters for some el…