The research group Data Mining and Machine Learning investigates novel approaches to exploratory data analysis, unsupervised, semi-supervised and supervised learning. We focus on methods for various data types including texts, graphs, high-dimensional feature vectors and other complex structures. We consider different tasks, e.g., representation learning, embedding, clustering, causality detection, classification and reinforcement learning.
The research group Data Mining and Machine Learning consists of eight work groups that are headed by their respective group leaders:
We are pleased to announce that our paper has been accepted to IEEE International Conference on Data Mining (ICDM 2026).
We are pleased to announce that three papers have been accepted to the forty-third International Conference on Machine Learning (ICML 2026)
We are proud to announce that our tutorial has been accepted at AAAI'26
