Hans Hagen, Non-Standard Metrics for Machine Learning

Euclidean Metrics and L2-Norms are the dominating standards
— . BUT are they good enough in all applications ?—-
I do not think so. Finslertyp metrics , which deal with point locations and directions show a lot of promise of being influential in important research areas.
The Lagrange Multiplier technique is a very powerfull tool assuming the “right energy functionals”.
What about energy functionals depending on non – standard metrics for GANs ( Generative Adversal Networks) ??
This would open the door for using Lagrange Multipliers.
To start a constructive and critical discussion is the goal of this talk .

How to join online

You can join online via Zoom, using the following link:
https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

Referent: Prof. Hans Hagen, Geometric Modeling Group, RPTU

Zeit: 11:00 Uhr

Ort: Hybrid (Room 32-349 and via Zoom)