Speaker
Simon Klüttermann
Description
My research focuses on ensemble methods for unsupervised learning tasks. Recently, I discovered a surprisingly effective approach for anomaly detection, which I named as a Polyra swarm. Upon further investigation, I found that Polyra exhibits a property analogous to the universal function approximation capability of neural networks. This insight has led me to explore an alternative paradigm where, instead of neural networks, we leverage Polyra swarms for learning tasks. Although this research is still in its early stages, and the talk will be very high level, such swarms offer a promising advantage in interpretability compared to traditional neural networks.
