Публикации 2020-2026

• 2026
  • M. Santoni, E. Raponi, A. Neumann, F. Neumann, M. Preuss, C. Doerr : “Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization”, Evolutionary Computation, vol. 34 (2), pp. 213–233, (Massachusetts Institute of Technology Press (MIT Press)) (2026)
• 2025
  • E. Raponi, N. Rakotonirina, J. Rapin, C. Doerr, O. Teytaud : “Optimizing With Low Budgets: A Comparison On the Black-Box Optimization Benchmarking Suite and OpenAI Gym”, IEEE Transactions on Evolutionary Computation, vol. 29 (1), pp. 91-101, (Institute of Electrical and Electronics Engineers) (2025)
  • M. Santoni, Ch. Dürr, C. Doerr, M. Preuss, E. Raponi : “Cascading CMA-ES Instances for Generating Input-diverse Solution Batches”, Proc. of the Genetic and Evolutionary Computation Conference (GECCO, Companion material, BBOB workshop), Malaga, Spain (2025)
• 2024
  • M. Santoni, E. Raponi, R. De Leone, C. Doerr : “Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB”, ACM Transactions on Evolutionary Learning and Optimization, vol. 4 (3), (ACM) (2024)
• 2023
  • M. Santoni, E. Raponi, R. De Leone, C. Doerr : “Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60”, GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation, Lisbon, Portugal, pp. 2390-2393, (ACM), (ISBN: 979-8-4007-0120-7) (2023)
  • C. Benjamins, E. Raponi, A. Janković, C. Doerr, M. Lindauer : “Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization”, GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation, Lisbon, Portugal, pp. 483-486, (ACM) (2023)
  • C. Benjamins, E. Raponi, A. Janković, C. Doerr, M. Lindauer : “Self-Adjusting Weighted Expected Improvement for Bayesian Optimization”, Proceedings of Machine Learning Research (PMLR), Potsdam, Germany (2023)
• 2022
  • C. Benjamins, E. Raponi, A. Janković, K. Van der Blom, M. Santoni, M. Lindauer, C. Doerr : “PI is back! Switching Acquisition Functions in Bayesian Optimization”, 2022 NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems, New Orleans, United States (2022)
  • C. Benjamins, A. Janković, E. Raponi, K. Van der Blom, M. Lindauer, C. Doerr : “Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis”, 6^th Workshop on Meta-Learning at NeurIPS 2022, New Orleans, United States (2022)
  • K. Antonov, E. Raponi, H. Wang, C. Doerr : “High Dimensional Bayesian Optimization with Kernel Principal Component Analysis”, 17^th Proceedings of Parallel Problem Solving from Nature - (PPSN) 2022, Dortmund, Germany, pp. 118-131 (2022)
• 2020
  • E. Raponi, H. Wang, M. Bujny, S. Boria, C. Doerr : “High Dimensional Bayesian Optimization Assisted by Principal Component Analysis”, Parallel Problem Solving from Nature – PPSN XVI, vol. 12269, Lecture Notes in Computer Science, Leiden, Netherlands, pp. 169-183, (Springer) (2020)