2 papers
math.ST2026
Scalable Operator Learning via Nyström Approximation With Denoising Applications
Naveen Gupta, Vaibhav Silmana, S. Sivananthan
In this paper, we study Nyström subsampling for vector-valued regression in vector-valued reproducing kernel Hilbert spaces. Standard kernel methods often suffer from prohibitive…
math.ST2026
Towards regularized learning from functional data with covariate shift
Markus Holzleitner, Sergiy Pereverzyev, Sergei V. Pereverzyev +2
This paper investigates a general regularization framework for unsupervised domain adaptation in vector-valued regression under the covariate shift assumption, utilizing vector-val…