The paper “Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings” by Adrian Kochsiek, Fritz Niesel, and Rainer Gemulla has been accepted at the 2022 ECML-PKDD European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in ...

We are happy to announce that team WBSG consisting of the PhD students Alexander Brinkmann and Ralph Peeters has won the ACM SIGMOD Programming Contest 2022. Altogether 55 teams from all over the world participated in the contest.

We are happy that the following papers have been accepted for the 31st International Joint Conference on Artificial Intelligence July 23–29, 2022 in Vienna (Acceptance Rate: 15%): Patrick Betz, Christian Meilicke and Heiner Stuckenschmidt: “Adversarial Explanations for Knowledge Graph Embeddings” ...

We are happy to announce that the paper “Exploiting Label Semantics for Rule-based Activity Recommendation in Business Process Modeling” by Diana Sola, Han van der Aa, Christian Meilicke and Heiner Stuckenschmidt has been accepted for the “Information Systems” Journal ( The paper can be found at: ...

We are happy to announce that the papers “Impact of the Characteristics of Multi-Source Entity Matching Tasks on the Performance of Active Learning Methods” by Anna Primpeli and Christian Bizer and the paper “Supervised Knowledge Aggregation for Knowledge Graph Completion” by Patrick Betz, Christian ...

The paper “NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access” by Alexander Renz-Wieland, Rainer Gemulla, Zoi Kaoudi, and Volker Markl  has been accepted at the 2022 ACM SIGMOD International Conference on Management of Data. Abstract: Parameter servers (PSs) ...

The paper “Parallel Training of Knowledge Graph Embedding Models: A Comparison of Techniques” by Adrian Kochsiek and Rainer Gemulla has been accepted at the 2022 Proceedings of the VLDB Endowment (PVLDB). Abstract: Knowledge graph embedding (KGE) models represent the entities and relations of a ...

The paper “Efficient Learning of Discrete-Continuous Computation Graphs” by David Friede and Mathias Niepert (NEC Research Labs) has been accepted for the 35th Conference on Neural Information Processing Systems (NeurIPS 2021).

Michael Pernpeinter, PhD Student in the AI Group successfully applied for a Fulbrigth Scholarship to visit Texas A&M University and work with Prof. Guni Sharon on Governance of Autonomous Multi-Agent Systems.