TU takes part in 36. International Conference on Machine Learning 2019
Machine learning experts from around the world will gather at the 36th International Conference on Machine Learning (ICML) to present the latest advances in machine learning understanding. The International Conference on Machine Learning is one of the most prestigious conferences for peer-reviewed research in Machine Learning, alongside NeurIPS, ICLR and others. And ICML is of the most relevant to Deep Learning (DL), although NeurIPS has a longer DL tradition and ICLR, being more focused, has a higher DL density. TU Darmstadt is the only German university among the top 50 contributing universities.
Despite the strong industrial interest and massive contributions from companies like Google, Microsoft or Facebook, the 2019 International Conference on Machine Learning remains an academic conference. Summing up the relative contribution of academia and industry for all papers (i.e. number of industrial/academic affiliations divided by number of total affiliations per paper), 77 percent of the contribution are from academia such as the TU Darmstadt. Researchers from the TU Darmstadt have co-authored six papers at ICML 2019, and the research will be presented in oral paper and poster sessions.
The researchers from the TU Darmstadt are also organizing and participating in workshops throughout the conference. The low acceptance rate of 23 percent allows to keep highest quality of all accepted and peer-reviewed papers.
Leading in AI
Professor Kristian Kersting, head of the Machine Learning group and initiator of the AI-DA network at the TU Darmstadt, and Professor Jan Peters, PhD, are excited. These numbers show that the TU Darmstadt succeeds in its mission of being a leading AI university not only in Europe but also in the world. Actually, the TU Darmstadt is the only University from Germany among the Top 50 contributing academic institutions at ICML 2019.
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Weitere Informationen:
http://proceedings.mlr.press/v97/stelzner19a.html
http://proceedings.mlr.press/v97/becker-ehmck19a.html
http://proceedings.mlr.press/v97/akrour19a.html
http://proceedings.mlr.press/v97/wildner19a.html
http://proceedings.mlr.press/v97/nam19a.html
http://proceedings.mlr.press/v97/becker19a.html