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ORCIDDiederick Vermetten
Diederick L. Vermetten
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- affiliation: Leiden University, The Netherlands
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2020 – today
- 2024
[j6]Anna V. Kononova, Diederick Vermetten, Fabio Caraffini
, Madalina-Andreea Mitran, Daniela Zaharie:
The Importance of Being Constrained: Dealing with Infeasible Solutions in Differential Evolution and Beyond. Evol. Comput. 32(1): 3-48 (2024)- [j5]Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. Evol. Comput. 32(3): 205-210 (2024) - [c40]Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov:
Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks. CEC 2024: 1-8 - [c39]Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke:
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization. GECCO 2024 - [c38]Carola Doerr, Diederick Vermetten, Jacob de Nobel, Thomas Bäck:
Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. GECCO Companion 2024: 791-799 - [c37]Martijn Halsema, Diederick Vermetten, Thomas Bäck, Niki van Stein:
A Critical Analysis of Raven Roost Optimization. GECCO Companion 2024: 1993-2001 - [c36]Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang:
Transfer Learning of Surrogate Models via Domain Affine Transformation. GECCO 2024 - [c35]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. GECCO 2024 - [c34]Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr:
Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler. PPSN (2) 2024: 20-35 - [c33]Jacob de Nobel, Diederick Vermetten, Anna V. Kononova, Ofer M. Shir, Thomas Bäck:
Avoiding Redundant Restarts in Multimodal Global Optimization. PPSN (2) 2024: 268-283 - [d14]Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke:
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization - Reproducibility Files. Zenodo, 2024
- [d13]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics - Reproducibility Files. Zenodo, 2024 - [d12]Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr:
Benchmarking Dynamic Binary Value Problems with IOHprofiler - Reproducibility files. Zenodo, 2024 - [d11]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB - Reproducibility and Additional Data. Version 2. Zenodo, 2024 [all versions] - [i44]Niki van Stein, Diederick Vermetten, Anna V. Kononova, Thomas Bäck:
Explainable Benchmarking for Iterative Optimization Heuristics. CoRR abs/2401.17842 (2024) - [i43]Haoran Yin, Diederick Vermetten, Furong Ye, Thomas H. W. Bäck, Anna V. Kononova:
Impact of spatial transformations on landscape features of CEC2022 basic benchmark problems. CoRR abs/2402.07654 (2024) - [i42]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-scale Benchmarking of Metaphor-based Optimization Heuristics. CoRR abs/2402.09800 (2024) - [i41]Manuel López-Ibáñez, Diederick Vermetten, Johann Dréo, Carola Doerr:
Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms. CoRR abs/2404.02031 (2024) - [i40]Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke:
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization. CoRR abs/2404.07539 (2024) - [i39]Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr:
Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler. CoRR abs/2404.15837 (2024) - [i38]Jacob de Nobel, Diederick Vermetten, Anna V. Kononova, Ofer M. Shir, Thomas Bäck:
Avoiding Redundant Restarts in Multimodal Global Optimization. CoRR abs/2405.01226 (2024) - [i37]Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov:
Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks. CoRR abs/2405.11964 (2024) - [i36]Jacob de Nobel, Diederick Vermetten, Thomas H. W. Bäck, Anna V. Kononova:
Sampling in CMA-ES: Low Numbers of Low Discrepancy Points. CoRR abs/2409.15941 (2024) - 2023
- [j4]Thomas H. W. Bäck, Anna V. Kononova, Bas van Stein, Hao Wang, Kirill A. Antonov, Roman T. Kalkreuth, Jacob de Nobel, Diederick Vermetten, Roy de Winter, Furong Ye:
Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. Evol. Comput. 31(2): 81-122 (2023) - [j3]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. IEEE Trans. Evol. Comput. 27(6): 1618-1632 (2023) - [c32]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts. AutoML 2023: 7/1-14 - [c31]Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten, Anja Jankovic, Ana Nikolikj, Urban Skvorc, Peter Korosec, Carola Doerr, Tome Eftimov:
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization. AutoML 2023: 11/1-17 - [c30]Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck:
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CEC 2023: 1-9 - [c29]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Pance Panov, Tome Eftimov, Carola Doerr:
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms. EvoApplications@EvoStar 2023: 253-268 - [c28]Diederick Vermetten, Hao Wang, Kevin Sim, Emma Hart:
To Switch or Not to Switch: Predicting the Benefit of Switching Between Algorithms Based on Trajectory Features. EvoApplications@EvoStar 2023: 335-350 - [c27]Fu Xing Long, Diederick Vermetten, Bas van Stein, Anna V. Kononova:
BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances. EvoApplications@EvoStar 2023: 380-395 - [c26]Roman Kalkreuth, Zdenek Vasícek, Jakub Husa, Diederick Vermetten, Furong Ye, Thomas Bäck:
General Boolean Function Benchmark Suite. FOGA 2023: 84-95 - [c25]Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
Assessing the Generalizability of a Performance Predictive Model. GECCO Companion 2023: 311-314 - [c24]Bas van Stein, Diederick Vermetten, Fabio Caraffini, Anna V. Kononova:
Deep BIAS: Detecting Structural Bias using Explainable AI. GECCO Companion 2023: 455-458 - [c23]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Saso Dzeroski, Tome Eftimov, Carola Doerr:
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems. GECCO Companion 2023: 495-498 - [c22]Roman Kalkreuth, Zdenek Vasícek, Jakub Husa, Diederick Vermetten, Furong Ye, Thomas Bäck:
Towards a General Boolean Function Benchmark Suite. GECCO Companion 2023: 591-594 - [c21]André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye, Thomas Bäck, Anna V. Kononova:
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. GECCO 2023: 856-863 - [c20]Diederick Vermetten, Fabio Caraffini, Anna V. Kononova, Thomas Bäck:
Modular Differential Evolution. GECCO 2023: 864-872 - [c19]Diederick Vermetten, Furong Ye, Carola Doerr:
Using Affine Combinations of BBOB Problems for Performance Assessment. GECCO 2023: 873-881 - [c18]Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye:
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion 2023: 938-945 - [c17]François Clément, Diederick Vermetten, Jacob de Nobel, Alexandre D. Jesus, Luís Paquete, Carola Doerr:
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. GECCO 2023: 1330-1338 - [c16]Diederick Vermetten, Manuel López-Ibáñez, Olaf Mersmann, Richard Allmendinger, Anna V. Kononova:
Analysis of modular CMA-ES on strict box-constrained problems in the SBOX-COST benchmarking suite. GECCO Companion 2023: 2346-2353 - [c15]Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein:
Challenges of ELA-Guided Function Evolution Using Genetic Programming. IJCCI 2023: 119-130 - [d10]François Clément, Diederick Vermetten, Jacob de Nobel, Alexandre D. Jesus, Luís Paquete, Carola Doerr:
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms - Code and Data. Zenodo, 2023 - [d9]Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein:
Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files. Zenodo, 2023 - [d8]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB - Reproducibility and Additional Data. Version 1. Zenodo, 2023 [all versions] - [d7]Diederick Vermetten, Furong Ye, Carola Doerr:
Using Affine Combinations of BBOB Problems for Performance Assessment - Code and Data. Zenodo, 2023 - [i35]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Pance Panov, Tome Eftimov, Carola Doerr:
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms. CoRR abs/2301.09876 (2023) - [i34]Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck:
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CoRR abs/2302.01464 (2023) - [i33]Diederick Vermetten, Hao Wang, Kevin Sim, Emma Hart:
To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features. CoRR abs/2302.09075 (2023) - [i32]Diederick Vermetten, Furong Ye, Carola Doerr:
Using Affine Combinations of BBOB Problems for Performance Assessment. CoRR abs/2303.04573 (2023) - [i31]Bas van Stein, Diederick Vermetten, Fabio Caraffini, Anna V. Kononova:
Deep-BIAS: Detecting Structural Bias using Explainable AI. CoRR abs/2304.01869 (2023) - [i30]Diederick Vermetten, Fabio Caraffini, Anna V. Kononova, Thomas Bäck:
Modular Differential Evolution. CoRR abs/2304.09524 (2023) - [i29]André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye, Thomas Bäck, Anna V. Kononova:
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. CoRR abs/2304.13117 (2023) - [i28]Diederick Vermetten, Manuel López-Ibáñez, Olaf Mersmann, Richard Allmendinger, Anna V. Kononova:
Analysis of modular CMA-ES on strict box-constrained problems in the SBOX-COST benchmarking suite. CoRR abs/2305.15102 (2023) - [i27]Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein:
Challenges of ELA-guided Function Evolution using Genetic Programming. CoRR abs/2305.15245 (2023) - [i26]Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
Assessing the Generalizability of a Performance Predictive Model. CoRR abs/2306.00040 (2023) - [i25]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts. CoRR abs/2306.10627 (2023) - [i24]François Clément, Diederick Vermetten, Jacob de Nobel, Alexandre D. Jesus, Luís Paquete, Carola Doerr:
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. CoRR abs/2306.16998 (2023) - [i23]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Saso Dzeroski, Tome Eftimov, Carola Doerr:
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems. CoRR abs/2306.17585 (2023) - [i22]Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten, Anja Jankovic, Ana Nikolikj, Urban Skvorc, Peter Korosec, Carola Doerr, Tome Eftimov:
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization. CoRR abs/2310.10685 (2023) - [i21]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts. CoRR abs/2312.11083 (2023) - [i20]Diederick Vermetten, Martin S. Krejca, Marius Lindauer, Manuel López-Ibáñez, Katherine M. Malan:
Synergizing Theory and Practice of Automated Algorithm Design for Optimization (Dagstuhl Seminar 23332). Dagstuhl Reports 13(8): 46-70 (2023) - 2022
- [j2]Diederick Vermetten, Bas van Stein, Fabio Caraffini, Leandro L. Minku, Anna V. Kononova:
BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain. IEEE Trans. Evol. Comput. 26(6): 1380-1393 (2022) - [j1]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics. ACM Trans. Evol. Learn. Optim. 2(1): 3:1-3:29 (2022) - [c14]Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr:
Trajectory-based Algorithm Selection with Warm-starting. CEC 2022: 1-8 - [c13]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. GECCO Companion 2022: 49-50 - [c12]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
The importance of landscape features for performance prediction of modular CMA-ES variants. GECCO 2022: 648-656 - [c11]Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck:
Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms. GECCO 2022: 867-875 - [c10]Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye:
Benchmarking and analyzing iterative optimization heuristics with IOH profiler. GECCO Companion 2022: 1334-1341 - [c9]Diederick Vermetten, Fabio Caraffini, Bas van Stein, Anna V. Kononova:
Using structural bias to analyse the behaviour of modular CMA-ES. GECCO Companion 2022: 1674-1682 - [c8]Furong Ye, Diederick Vermetten, Carola Doerr, Thomas Bäck:
Non-elitist Selection Can Improve the Performance of Irace. PPSN (1) 2022: 32-45 - [c7]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr:
Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. PPSN (1) 2022: 46-60 - [d6]Anja Jankovic, Ana Kostovska, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr:
Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data. Zenodo, 2022 - [d5]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules - Data. Zenodo, 2022 - [d4]Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck:
Analyzing the Impact of Undersampling on the Benchmarkingand Configuration of Evolutionary Algorithms - Dataset. Zenodo, 2022 - [d3]Diederick Vermetten, Hao Wang, Kevin Sim, Emma Hart:
To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features - Dataset. Zenodo, 2022 - [d2]Furong Ye, Diederick Vermetten, Carola Doerr, Thomas Bäck:
Data Sets for the study "Non-Elitist Selection Can Improve the Performance of Irace". Zenodo, 2022 - [i19]Anna V. Kononova, Diederick Vermetten, Fabio Caraffini, Madalina-Andreea Mitran, Daniela Zaharie:
The importance of being constrained: dealing with infeasible solutions in Differential Evolution and beyond. CoRR abs/2203.03512 (2022) - [i18]Furong Ye, Diederick L. Vermetten, Carola Doerr, Thomas Bäck:
Non-Elitist Selection among Survivor Configurations can Improve the Performance of Irace. CoRR abs/2203.09227 (2022) - [i17]Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr:
Trajectory-based Algorithm Selection with Warm-starting. CoRR abs/2204.06397 (2022) - [i16]Dominik Schröder, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points. CoRR abs/2204.06539 (2022) - [i15]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants. CoRR abs/2204.07431 (2022) - [i14]Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck:
Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms. CoRR abs/2204.09353 (2022) - [i13]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr:
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features. CoRR abs/2204.09483 (2022) - [i12]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2211.11332 (2022) - [i11]Fu Xing Long, Diederick Vermetten, Bas van Stein, Anna V. Kononova:
BBOB Instance Analysis: Landscape Properties and Algorithm Performance across Problem Instances. CoRR abs/2211.16318 (2022) - 2021
- [c6]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: optimization algorithm benchmarking ontology. GECCO Companion 2021: 239-240 - [c5]Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Is there anisotropy in structural bias? GECCO Companion 2021: 1243-1250 - [c4]Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. GECCO Companion 2021: 1375-1384 - [d1]Diederick Vermetten, Hao Wang, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer version 0.1.6.1 + example datasets. Zenodo, 2021 - [i10]Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules. CoRR abs/2102.12905 (2021) - [i9]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2104.11889 (2021) - [i8]Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Is there Anisotropy in Structural Bias? CoRR abs/2105.04480 (2021) - [i7]Nils van den Honert, Diederick Vermetten, Anna V. Kononova:
Benchmarking the Status of Default Pseudorandom Number Generators in Common Programming Languages. CoRR abs/2109.12997 (2021) - [i6]Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. CoRR abs/2111.04077 (2021) - 2020
- [c3]Diederick Vermetten, Hao Wang, Thomas Bäck, Carola Doerr:
Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. GECCO 2020: 654-662 - [c2]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. GECCO 2020: 903-912 - [i5]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case. CoRR abs/2006.06586 (2020) - [i4]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. CoRR abs/2007.03953 (2020) - [i3]Noor H. Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter:
Squirrel: A Switching Hyperparameter Optimizer. CoRR abs/2012.08180 (2020)
2010 – 2019
- 2019
- [c1]Diederick Vermetten, Sander van Rijn, Thomas Bäck, Carola Doerr:
Online selection of CMA-ES variants. GECCO 2019: 951-959 - [i2]Diederick Vermetten, Sander van Rijn, Thomas Bäck, Carola Doerr:
Online Selection of CMA-ES Variants. CoRR abs/1904.07801 (2019) - [i1]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. CoRR abs/1912.05899 (2019)
Coauthor Index
Thomas Bäck
aka: Thomas H. W. Bäck
aka: Thomas H. W. Bäck
[j5] [c38] [c37] [c36] [c35] [c34] [c33] [d13] [d12] [d11] [i44] [i43] [i42] [i39] [i38] [i36] [j4] [c32] [c30] [c26] [c22] [c21] [c20] [c18] [c15] [d9] [d8] [i34] [i30] [i29] [i27] [i25] [i21] [j1] [c13] [c11] [c10] [c8] [d4] [d2] [i18] [i16] [i14] [c5] [c4] [d1] [i10] [i8] [i6] [c3] [c2] [i5] [i4] [c1] [i2] [i1]
[j5] [c40] [c39] [c38] [c35] [c34] [d14] [d13] [d12] [d11] [i42] [i41] [i40] [i39] [i37] [j3] [c32] [c31] [c29] [c25] [c23] [c19] [c18] [c17] [d10] [d8] [d7] [i35] [i32] [i26] [i25] [i24] [i23] [i22] [i21] [j1] [c14] [c13] [c12] [c11] [c10] [c8] [c7] [d6] [d5] [d4] [d2] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [c6] [c4] [d1] [i10] [i9] [i6] [c3] [c2] [i5] [i4] [i3] [c1] [i2] [i1]
Niki van Stein
aka: Bas van Stein
aka: Bas van Stein
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last updated on 2024-10-30 21:33 CET by the dblp team
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