Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio M König, HH Hoos, JN Rijn Machine Learning 111 (12), 4565-4584, 2022 | 9 | 2022 |
Critically assessing the state of the art in neural network verification M König, AW Bosman, HH Hoos, JN van Rijn Journal of Machine Learning Research 25 (12), 1-53, 2024 | 7 | 2024 |
Towards Algorithm-Agnostic Uncertainty Estimation: Predicting Classification Error in an Automated Machine Learning Setting M König, HH Hoos, JN van Rijn 7th ICML Workshop on Automated Machine Learning, 2020 | 7 | 2020 |
Hyper-parameter optimization for latent spaces B Veloso, L Caroprese, M König, S Teixeira, G Manco, HH Hoos, J Gama Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 4 | 2021 |
Speeding Up Neural Network Verification via Automated Algorithm Configuration M König, HH Hoos, JN van Rijn ICLR Workshop on Security and Safety in Machine Learning Systems, 2021 | 4 | 2021 |
Critically Assessing the State of the Art in CPU-based Local Robustness Verification M König, AW Bosman, HH Hoos, JN van Rijn Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI …, 2022 | 3 | 2022 |
Accelerating Adversarially Robust Model Selection for Deep Neural Networks via Racing M König, HH Hoos, JN van Rijn Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), 2024 | 1 | 2024 |
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks M König, X Zhang, HH Hoos, M Kwiatkowska, JN van Rijn Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | | 2024 |
Modelling Concept Drift in Dynamic Data Streams for Recommender Systems L Caroprese, F Pisani, BM Veloso, M Konig, G Manco, H Hoos, J Gama ACM Transactions on Recommender Systems, 2024 | | 2024 |