{"id":1142,"date":"2023-06-20T10:48:41","date_gmt":"2023-06-20T10:48:41","guid":{"rendered":"https:\/\/dataninja.nrw\/?page_id=1142"},"modified":"2024-03-21T08:56:55","modified_gmt":"2024-03-21T08:56:55","slug":"dn-spring-school-2023-online-proceedings","status":"publish","type":"page","link":"https:\/\/dataninja.nrw\/?page_id=1142","title":{"rendered":"DataNinja Spring School 2023 Online Proceedings"},"content":{"rendered":"\n

DataNinja Spring School 2023 Online Proceedings<\/h1>\n\n\n\n

Welcome to the online proceedings of the DataNinja Spring School 2023 – “Trustworthy AI: Building Safe and Reliable Solutions”.
During our Spring School, young talents in AI had the opportunity to showcase their own work in the virtual poster session.
This page serves as a repository for the corresponding abstracts and poster files.<\/p>\n\n\n\n

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Unsupervised Neural Network Verification<\/a><\/h4>\n\n\n\n

Benedikt B\u00f6ing1<\/sup> & Emmanuel M\u00fcller1<\/sup>
1 <\/sup>Chair of Data Science and Data Engineering, Technical Uni- versity of Dortmund, Dortmund, Germany<\/p>\n\n\n\n

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Continual Hyperband<\/a><\/h4>\n\n\n\n

Jasmin Brandt1<\/sup>, Marcel Wever2<\/sup>, Dimitrios Iliadis3<\/sup>, Viktor Bengs2<\/sup> & Eyke H\u00fcllermeier2<\/sup>
1 <\/sup>University of Paderborn, Paderborn, Germany
2<\/sup> University of Munich, Munich, Germany
3<\/sup> Ghent University, Ghent, Belgium<\/p>\n<\/div><\/div>\n\n\n\n

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Provably Bounding Neural Network Preimages<\/a><\/h4>\n\n\n\n

Suhas Kotha1<\/sup>, Christopher Brix2<\/sup>, Zico Kolter1,4<\/sup>, Krishnamurthy (Dj) Dvijotham3<\/sup> & Huan Zhang1<\/sup>
1<\/sup> Carnegie Mellon University, Pittsburgh PA, USA
2<\/sup> RWTH Aachen University, Aachen, Germany
3<\/sup> Google Research, Brain Team
4<\/sup> Bosch Center for AI<\/p>\n<\/div><\/div>\n\n\n\n

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An Investigation of the Vulnerabilities and Effects of Prompt-Tuning
to Pre-Trained Language Models<\/a><\/h4>\n\n\n\n

Fotini Deligiannaki1<\/sup> & Arne Peter Raulf1<\/sup>
1<\/sup> Institute for AI Safety and Security, German Aerospace Center, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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Finding the Relevant Samples for Decision Trees in Reinforcement Learning<\/a><\/h4>\n\n\n\n

Raphael C. Engelhardt1<\/sup>, Moritz Lange2<\/sup>, Laurenz Wiskott2<\/sup> & Wolfgang Konen1<\/sup>
1<\/sup> Cologne Institute of Computer Science, TH K\u00f6ln, K\u00f6ln, Germany
2<\/sup> Institute for Neural Computation, Ruhr-University Bochum, Bochum, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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Graph Learning by Dynamic Sampling <\/a><\/h4>\n\n\n\n

Luca Hermes1<\/sup>, Aleksei Liuliakov1<\/sup> & Malte Schilling2<\/sup>
1<\/sup> Machine Learning Group, Bielefeld University, Bielefeld, Germany
2<\/sup> Autonomous Intelligent Systems Group, University of M\u00fcnster, M\u00fcnster, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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Unsupervised DeepView: Global Explainability of Uncertainties for High Dimensional Data<\/a><\/h4>\n\n\n\n

Carina Newen1<\/sup> & Emmanuel M\u00fcller1<\/sup>
1<\/sup> Research Center Trustworthy Data Science and Security, Technical University of Dortmund, Dortmund, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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Identifying and Explaining Undesirable Traces in Business Processes Using Descriptive and Predictive Analysis<\/a><\/h4>\n\n\n\n

Ali Norouzifar1<\/sup>
1<\/sup> Process and Data Science Group (PADS), RWTH Aachen University, Aachen, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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LU-Net: Invertible Neural Networks Based on Matrix Factorization<\/a><\/h4>\n\n\n\n

Robin Chan1<\/sup>, Sarina Penquitt2<\/sup> & Hanno Gottschalk2<\/sup>
1<\/sup> Machine Learning Group, Bielefeld University, Bielefeld, Germany
2<\/sup> IZMD, University of Wuppertal, Wuppertal, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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Off-line Learning Analysis for Soft Committee Machines with GELU Activation<\/a><\/h4>\n\n\n\n

Frederieke Richert1<\/sup>, Michiel Straat2<\/sup> & Michael Biehl1<\/sup>
1<\/sup> Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, The Netherlands
2<\/sup> Center for Cognitive Interaction Technology, Bielefeld University, Bielefeld, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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Evaluating Spiking Neural Network Models: A Comparative Performance Analysis<\/a><\/h4>\n\n\n\n

Sanaullah1<\/sup>, Shamini Koravuna2<\/sup>, Ulrich R\u00fcckert2<\/sup> & Thorsten Jungeblut1<\/sup>
1<\/sup> Bielefeld University of Applied Science, Bielefeld, Germany
2<\/sup> University of Bielefeld, Bielefeld, Germany<\/p>\n<\/div><\/div>\n\n\n\n

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