| Exploratory landscape analysis is strongly sensitive to the sampling strategy Q Renau, C Doerr, J Dreo, B Doerr Parallel Problem Solving from Nature–PPSN XVI: 16th International Conference …, 2020 | 74 | 2020 |
| Towards explainable exploratory landscape analysis: extreme feature selection for classifying BBOB functions Q Renau, J Dreo, C Doerr, B Doerr Applications of Evolutionary Computation: 24th International Conference …, 2021 | 47 | 2021 |
| Expressiveness and robustness of landscape features Q Renau, J Dreo, C Doerr, B Doerr Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 37 | 2019 |
| Linear matrix factorization embeddings for single-objective optimization landscapes T Eftimov, G Popovski, Q Renau, P Korošec, C Doerr 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 775-782, 2020 | 16 | 2020 |
| On the Utility of Probing Trajectories for Algorithm-Selection Q Renau, E Hart International Conference on the Applications of Evolutionary Computation …, 2024 | 5 | 2024 |
| Applications of Evolutionary Computation: 24th International Conference, EvoApplications 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings PA Castillo, JLJ Laredo Springer Nature, 2021 | 5 | 2021 |
| Landscape-Aware Selection of Metaheuristics for the Optimization of Radar Networks Q Renau Institut Polytechnique de Paris, 2022 | 4 | 2022 |
| Automated algorithm selection for radar network configuration Q Renau, J Dreo, A Peres, Y Semet, C Doerr, B Doerr Proceedings of the Genetic and Evolutionary Computation Conference, 1263-1271, 2022 | 3 | 2022 |
| Experimental Data Set for the study "Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy" Q Renau, C Doerr, J Dreo, B Doerr 10.5281/zenodo.3886816, 2020 | 3 | 2020 |
| Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples Q Renau, E Hart Proceedings of the Genetic and Evolutionary Computation Conference, 1026-1035, 2024 | 2 | 2024 |
| Towards optimisers thatKeep Learning' E Hart, I Miguel, C Stone, Q Renau Proceedings of the Companion Conference on Genetic and Evolutionary …, 2023 | 2 | 2023 |
| Identifying Easy Instances to Improve Efficiency of ML Pipelines for Algorithm-Selection Q Renau, E Hart International Conference on Parallel Problem Solving from Nature, 70-86, 2024 | 1 | 2024 |
| Evaluating the robustness of deep-learning algorithm-selection models by evolving adversarial instances E Hart, Q Renau, K Sim, M Alissa International Conference on Parallel Problem Solving from Nature, 121-136, 2024 | 1 | 2024 |
| Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model Q Renau, E Hart arXiv preprint arXiv:2501.11414, 2025 | | 2025 |
| Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing K Sim, Q Renau, E Hart arXiv preprint arXiv:2501.11411, 2025 | | 2025 |
| Stalling in Space: Attractor Analysis for any Algorithm SL Thomson, Q Renau, D Vermetten, E Hart, N van Stein, AV Kononova arXiv preprint arXiv:2412.15848, 2024 | | 2024 |
| Ealain: A Camera Simulation Tool to Generate Instances for Multiple Classes of Optimisation Problem Q Renau, J Dreo, E Hart Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2024 | | 2024 |
| An Evaluation of Domain-Agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation C Stone, Q Renau, I Miguel, E Hart International Conference on Learning and Intelligent Optimization, 399-414, 2024 | | 2024 |
| Dataset: Gecco 2022 Automated Algorithm Selection for Radar Network Configuration Q Renau, J Dreo, A Peres, Y Semet, C Doerr, B Doerr 10.5281/zenodo.5963886, 2022 | | 2022 |
| Exploratory Landscape Analysis Feature Values for the 24 Noiseless BBOB Functions Q Renau, J Dreo, C Doerr, B Doerr 10.5281/zenodo.4449934, 2021 | | 2021 |
Carola DoerrCNRS research director (DR) at Sorbonne Université, Paris, FranceEmail yang diverifikasi di mpi-inf.mpg.de