research
∙
11/16/2022
Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem
We consider the problem of learning a linear operator θ between two Hilb...
share
research
∙
08/02/2022
Optimal Rates for Regularized Conditional Mean Embedding Learning
We address the consistency of a kernel ridge regression estimate of the ...
research
∙
12/23/2020
Nonparametric approximation of conditional expectation operators
Given the joint distribution of two random variables X,Y on some second ...
research
∙
04/02/2020
Kernel autocovariance operators of stationary processes: Estimation and convergence
We consider autocovariance operators of a stationary stochastic process ...
research
∙
05/27/2019
Kernel Conditional Density Operators
We introduce a conditional density estimation model termed the condition...
research
∙
04/16/2019
Kernel canonical correlation analysis approximates operators for the detection of coherent structures in dynamical data
We illustrate relationships between classical kernel-based dimensionalit...
research
∙
07/24/2018
Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces
Reproducing kernel Hilbert spaces (RKHSs) play an important role in many...
research
∙
03/29/2018