30 citations · 63 across the 6 of their papers we have counts for
6 papers
Adaptive Clustering Using Kernel Density Estimators
Ingo Steinwart, Bharath K. Sriperumbudur, Philipp Thomann
We derive and analyze a generic, recursive algorithm for estimating all splits in a finite cluster tree as well as the corresponding clusters. We further investigate statistical pr…
liquidSVM: A Fast and Versatile SVM package
Ingo Steinwart, Philipp Thomann
liquidSVM is a package written in C++ that provides SVM-type solvers for various classification and regression tasks. Because of a fully integrated hyper-parameter selection, very…
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…
Spatial Decompositions for Large Scale SVMs
Philipp Thomann, Ingrid Blaschzyk, Mona Meister +1
Although support vector machines (SVMs) are theoretically well understood, their underlying optimization problem becomes very expensive, if, for example, hundreds of thousands of s…
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…
Continuity and anomalous fluctuations in random walks in dynamic random environments: numerics, phase diagrams and conjectures
L. Avena, P. Thomann
We perform simulations for one dimensional continuous-time random walks in two dynamic random environments with fast (independent spin-flips) and slow (simple symmetric exclusion)…