Incubator Projects



In finite-Dimensional Supervised Least Squares Learning as a Noncompact Regularized Inverse Problem

Project Heads

Péter Koltai

Project Members

Mattes Mollenhauer

Project Duration

01.01.2022 – 31.12.2022

Located at

FU Berlin


We propose an approach to spectral regularization algorithms for kernel-based supervised learning with in finite-dimensional response variables. Recent research shows that this scenario enjoys widespread practical use. However, virtually no results exist due to the mathematical complexity compared to the finite-dimensional learning settings investigated so far.

Project Webpages

Selected Publications

Selected Pictures

Please insert any kind of pictures (photos, diagramms, simulations, graphics) related to the project in the above right field (Image with Text), by choosing the green plus image on top of the text editor. (You will be directed to the media library where you can add new files.)
(We need pictures for a lot of purposes in different contexts, like posters, scientific reports, flyers, website,…
Please upload pictures that might be just nice to look at, illustrate, explain or summarize your work.)

As Title in the above form please add a copyright.

And please give a short description of the picture and the context in the above textbox.

Don’t forget to press the “Save changes” button at the bottom of the box.

If you want to add more pictures, please use the “clone”-button at the right top of the above grey box.