| Temporal convolutional autoencoder for unsupervised anomaly detection in time series M Thill, W Konen, H Wang, T Bäck Applied Soft Computing 112, 107751, 2021 | 164 | 2021 |
| Performance comparison of optimization methods on variational quantum algorithms X Bonet-Monroig, H Wang, D Vermetten, B Senjean, C Moussa, T Bäck, ... Physical Review A 107 (3), 032407, 2023 | 101 | 2023 |
| A new acquisition function for Bayesian optimization based on the moment-generating function H Wang, B van Stein, M Emmerich, T Back 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017 | 97 | 2017 |
| A multicriteria generalization of bayesian global optimization M Emmerich, K Yang, A Deutz, H Wang, CM Fonseca Advances in Stochastic and Deterministic Global Optimization, 229-242, 2016 | 87 | 2016 |
| Benchmarking discrete optimization heuristics with IOHprofiler C Doerr, F Ye, N Horesh, H Wang, OM Shir, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 81 | 2019 |
| IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics C Doerr, H Wang, F Ye, S van Rijn, T Bäck arXiv preprint arXiv:1810.05281, 2018 | 74 | 2018 |
| Evolving the structure of evolution strategies S van Rijn, H Wang, M van Leeuwen, T Bäck 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016 | 62 | 2016 |
| IOHanalyzer: Detailed performance analyses for iterative optimization heuristics H Wang, D Vermetten, F Ye, C Doerr, T Bäck ACM Transactions on Evolutionary Learning and Optimization 2 (1), 1-29, 2022 | 61 | 2022 |
| Cluster-based Kriging approximation algorithms for complexity reduction B van Stein, H Wang, W Kowalczyk, M Emmerich, T Bäck Applied Intelligence 50 (3), 778-791, 2020 | 54 | 2020 |
| Optimally weighted cluster kriging for big data regression B Stein, H Wang, W Kowalczyk, T Bäck, M Emmerich International symposium on intelligent data analysis, 310-321, 2015 | 54 | 2015 |
| Towards analyzing multimodality of continuous multiobjective landscapes P Kerschke, H Wang, M Preuss, C Grimme, A Deutz, H Trautmann, ... Parallel Problem Solving from Nature–PPSN XIV: 14th International Conference …, 2016 | 48 | 2016 |
| Automated Machine Learning for EEG-Based Classification of Parkinson’s Disease Patients M Koch, V Geraedts, H Wang, M Tannemaat, T Bäck 2019 IEEE International Conference on Big Data (Big Data), 4845-4852, 2019 | 47 | 2019 |
| Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules J de Nobel, D Vermetten, H Wang, C Doerr, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 46 | 2021 |
| Machine learning for automated EEG-based biomarkers of cognitive impairment during Deep Brain Stimulation screening in patients with Parkinson’s Disease VJ Geraedts, M Koch, MF Contarino, HAM Middelkoop, H Wang, ... Clinical Neurophysiology 132 (5), 1041-1048, 2021 | 45 | 2021 |
| Evolution Strategies M Emmerich, OM Shir, H Wang Handbook of Heuristics, 1-31, 2018 | 44 | 2018 |
| Per-run algorithm selection with warm-starting using trajectory-based features A Kostovska, A Jankovic, D Vermetten, J de Nobel, H Wang, T Eftimov, ... Parallel Problem Solving from Nature–PPSN XVII: 17th International …, 2022 | 43 | 2022 |
| High dimensional Bayesian optimization assisted by principal component analysis E Raponi, H Wang, M Bujny, S Boria, C Doerr Parallel Problem Solving from Nature–PPSN XVI: 16th International Conference …, 2020 | 43 | 2020 |
| Bayesian performance analysis for black-box optimization benchmarking B Calvo, OM Shir, J Ceberio, C Doerr, H Wang, T Bäck, JA Lozano Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 41 | 2019 |
| The set-based hypervolume newton method for bi-objective optimization VAS Hernández, O Schütze, H Wang, A Deutz, M Emmerich IEEE transactions on cybernetics 50 (5), 2186-2196, 2018 | 36 | 2018 |
| Hypervolume indicator gradient ascent multi-objective optimization H Wang, A Deutz, T Bäck, M Emmerich Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO …, 2017 | 36 | 2017 |
Thomas BäckProfessor of Computer Science, Leiden University; Chief Scientist, NORCE Research Centre, NorwayVerified email at liacs.leidenuniv.nl
