25 citations · 58 across the 16 of their papers we have counts for
4 papers · 1 filter
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
Dimitri Meunier, Zikai Shen, Mattes Mollenhauer +2
We study theoretical properties of a broad class of regularized algorithms with vector-valued output. These spectral algorithms include kernel ridge regression, kernel principal co…
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm
Zhu Li, Dimitri Meunier, Mattes Mollenhauer +1
We present the first optimal rates for infinite-dimensional vector-valued ridge regression on a continuous scale of norms that interpolate between and the hypothesis space, w…
Optimal Rates for Regularized Conditional Mean Embedding Learning
Zhu Li, Dimitri Meunier, Mattes Mollenhauer +1
We address the consistency of a kernel ridge regression estimate of the conditional mean embedding (CME), which is an embedding of the conditional distribution of given int…
On Hyperparameter Search in Cluster Ensembles
Luzie Helfmann, Johannes von Lindheim, Mattes Mollenhauer +1
Quality assessments of models in unsupervised learning and clustering verification in particular have been a long-standing problem in the machine learning research. The lack of rob…