Publications 2020-2024
Toutes
Articles de revues
Communications
Posters
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)
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, (Institute of Electrical and Electronics Engineers) (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 ”, 6th 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 ”, 17th 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)