| Escaping large deceptive basins of attraction with heavy-tailed mutation operators T Friedrich, F Quinzan, M Wagner Proceedings of the Genetic and Evolutionary Computation Conference, 293-300, 2018 | 57 | 2018 |
| Greedy maximization of functions with bounded curvature under partition matroid constraints T Friedrich, A Göbel, F Neumann, F Quinzan, R Rothenberger Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2272-2279, 2019 | 46 | 2019 |
| Heavy-tailed mutation operators in single-objective combinatorial optimization T Friedrich, A Göbel, F Quinzan, M Wagner International Conference on Parallel Problem Solving from Nature, 134-145, 2018 | 41 | 2018 |
| Evolutionary algorithms and submodular functions: benefits of heavy-tailed mutations F Quinzan, A Göbel, M Wagner, T Friedrich Natural Computing 20 (3), 561-575, 2021 | 19 | 2021 |
| Drcfs: Doubly robust causal feature selection F Quinzan, A Soleymani, P Jaillet, CR Rojas, S Bauer International Conference on Machine Learning, 28468-28491, 2023 | 17 | 2023 |
| Learning counterfactually invariant predictors F Quinzan, C Casolo, K Muandet, Y Luo, N Kilbertus arXiv preprint arXiv:2207.09768, 2022 | 15 | 2022 |
| Evolutionary algorithms and submodular functions: Benefits of heavy-tailed mutations T Friedrich, A Göbel, F Quinzan, M Wagner arXiv preprint arXiv:1805.10902, 2018 | 9 | 2018 |
| Diffusion-based causal representation learning AM Karimi Mamaghan, A Dittadi, S Bauer, KH Johansson, F Quinzan Entropy 26 (7), 556, 2024 | 8 | 2024 |
| Robust reinforcement learning from human feedback for large language models fine-tuning K Ye, H Zhou, J Zhu, F Quinzan, C Shi arXiv preprint arXiv:2504.03784, 2025 | 6 | 2025 |
| Fast feature selection with fairness constraints F Quinzan, R Khanna, M Hershcovitch, S Cohen, DG Waddington, ... arXiv preprint arXiv:2202.13718, 2022 | 6 | 2022 |
| Doubly Robust Alignment for Large Language Models E Xu, K Ye, H Zhou, L Zhu, F Quinzan, C Shi arXiv preprint arXiv:2506.01183, 2025 | 5 | 2025 |
| Approximating optimization problems using EAs on scale-free networks A Chauhan, T Friedrich, F Quinzan Proceedings of the Genetic and Evolutionary Computation Conference, 235-242, 2017 | 5 | 2017 |
| Resampling vs recombination: A statistical run time estimation T Friedrich, T Kötzing, F Quinzan, AM Sutton Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic …, 2017 | 5 | 2017 |
| When Should We Orchestrate Multiple Agents? U Bhatt, S Kapoor, M Upadhyay, I Sucholutsky, F Quinzan, KM Collins, ... arXiv preprint arXiv:2503.13577, 2025 | 4 | 2025 |
| Adaptive sampling for fast constrained maximization of submodular functions F Quinzan, V Doskoc, A Göbel, T Friedrich International Conference on Artificial Intelligence and Statistics, 964-972, 2021 | 4 | 2021 |
| Non-monotone submodular maximization with multiple knapsacks in static and dynamic settings V Doskoč, T Friedrich, A Göbel, F Neumann, A Neumann, F Quinzan arXiv preprint arXiv:1911.06791, 2019 | 4 | 2019 |
| Learning decision policies with instrumental variables through double machine learning D Shao, A Soleymani, F Quinzan, M Kwiatkowska arXiv preprint arXiv:2405.08498, 2024 | 3 | 2024 |
| Doubly robust structure identification from temporal data E Angelis, F Quinzan, A Soleymani, P Jaillet, S Bauer arXiv preprint arXiv:2311.06012, 2023 | 3 | 2023 |
| Improving the run time of the (1+ 1) evolutionary algorithm with Luby sequences T Friedrich, T Kötzing, F Quinzan, AM Sutton Proceedings of the Genetic and Evolutionary Computation Conference, 301-308, 2018 | 3 | 2018 |
| AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis H Ma, F Quinzan, T Willem, S Bauer arXiv preprint arXiv:2504.19621, 2025 | 1 | 2025 |
Tobias FriedrichChair for Algorithm Engineering, Hasso Plattner Institute, Potsdam, GermanyVerified email at hpi.de
