The program focused on the following four themes:
- Optimization: How and why can deep models be fit to observed (training) data?
- Generalization: Why do these trained models work well on similar but unobserved (test) data?
- Robustness: How can we analyze and improve the performance of these models when applied outside their intended conditions?
- Generative methods: How can deep learning be used to model probability distributions?
Machine Learning Summer School (MLSS) is a course about modern methods of statistical machine learning and inference. It presents topics which are at the cor...
M. Alam, P. Groth, P. Hitzler, H. Paulheim, H. Sack, and V. Tresp. CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020, page 3523--3524. ACM, (2020)
M. Vafaie, O. Bruns, D. Dess\`ı, N. Pilz, and H. Sack. Proceedings of the 6th International Workshop on Computational History (HistoInformatics 2021) co-located with ACM/IEEE Joint Conference on Digital Libraries 2021 (JCDL 2021), Online event, September 30-October 1, 2021, volume 2981 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)