6 papers
DisCoMBO: Steering Expert-in-the-Loop Black-Box Optimization via Distributional Conformance
Jonas Seng, Bennet Wittelsbach, Kristian Kersting
Sequential Model-Based Optimization (SMBO) traditionally relies on Bayesian or ensembling surrogates for uncertainty quantification. While historically treated as fully data-driven…
All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams
Marco Pegoraro, Jonas Seng, Dustin Heller +2
Disciplines such as business process management and process mining aid organizations by discovering insights about processes on the basis of recorded event data. However, an obstac…
Hyperparameter Optimization via Interacting with Probabilistic Circuits
Jonas Seng, Fabrizio Ventola, Zhongjie Yu +1
Despite the growing interest in designing truly interactive hyperparameter optimization (HPO) methods, to date, only a few allow to include human feedback. Existing interactive Bay…
Guidelines for the Quality Assessment of Energy-Aware NAS Benchmarks
Nick Kocher, Christian Wassermann, Leona Hennig +5
Neural Architecture Search (NAS) accelerates progress in deep learning through systematic refinement of model architectures. The downside is increasingly large energy consumption d…
Characteristic Circuits
Zhongjie Yu, Martin Trapp, Kristian Kersting
In many real-world scenarios, it is crucial to be able to reliably and efficiently reason under uncertainty while capturing complex relationships in data. Probabilistic circuits (P…
SPARE: A Single-Pass Neural Model for Relational Databases
Benjamin Hilprecht, Kristian Kersting, Carsten Binnig
While there has been extensive work on deep neural networks for images and text, deep learning for relational databases (RDBs) is still a rather unexplored field. One direction tha…