267 citations · 813 across the 34 of their papers we have counts for
5 papers · 1 filter
Strictly proper kernel scores and characteristic kernels on compact spaces
Ingo Steinwart, Johanna F. Ziegel
Strictly proper kernel scores are well-known tool in probabilistic forecasting, while characteristic kernels have been extensively investigated in the machine learning literature.…
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…
Learning Rates for Kernel-Based Expectile Regression
Muhammad Farooq, Ingo Steinwart
Conditional expectiles are becoming an increasingly important tool in finance as well as in other areas of applications. We analyse a support vector machine type approach for estim…
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…
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm
Simon Fischer, Ingo Steinwart
Learning rates for least-squares regression are typically expressed in terms of -norms. In this paper we extend these rates to norms stronger than the -norm without requi…