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ORCIDCarola Doerr
Carola Winzen
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- affiliation: Sorbonne Université, CNRS, LIP6, Paris, France
- affiliation (former): Max Planck Institute for Informatics, Saarbrücken, Germany
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2020 – today
- 2024
[j45]Carola Doerr, Duri Andrea Janett, Johannes Lengler:
Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions. Algorithmica 86(10): 3115-3152 (2024)- [j44]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) - [j43]François Clément, Carola Doerr, Luís Paquete:
Heuristic approaches to obtain low-discrepancy point sets via subset selection. J. Complex. 83: 101852 (2024) - [j42]Maria Laura Santoni, Elena Raponi, Renato De Leone, Carola Doerr:
Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB. ACM Trans. Evol. Learn. Optim. 4(3): 17:1-17:33 (2024) - [c133]Ana Nikolikj, Ana Kostovska, Gjorgjina Cenikj, Carola Doerr, Tome Eftimov:
Generalization Ability of Feature-Based Performance Prediction Models: A Statistical Analysis Across Benchmarks. CEC 2024: 1-8 - [c132]Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov:
Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks. CEC 2024: 1-8 - [c131]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 - [c130]Carola Doerr, Diederick Vermetten, Jacob de Nobel, Thomas Bäck:
Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. GECCO Companion 2024: 791-799 - [c129]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. GECCO 2024 - [c128]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 - [c127]Moritz Seiler, Urban Skvorc, Gjorgjina Cenikj, Carola Doerr, Heike Trautmann:
Learned Features vs. Classical ELA on Affine BBOB Functions. PPSN (2) 2024: 137-153 - [c126]Konstantin Dietrich, Raphael Patrick Prager, Carola Doerr, Heike Trautmann:
Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box Optimization. PPSN (2) 2024: 154-169 - [d20]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
- [d19]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics - Reproducibility Files. Zenodo, 2024 - [d18]Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr:
Benchmarking Dynamic Binary Value Problems with IOHprofiler - Reproducibility files. Zenodo, 2024 - [d17]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB - Reproducibility and Additional Data. Version 2. Zenodo, 2024 [all versions] - [i125]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-scale Benchmarking of Metaphor-based Optimization Heuristics. CoRR abs/2402.09800 (2024) - [i124]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) - [i123]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) - [i122]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) - [i121]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) - [i120]Ana Nikolikj, Ana Kostovska, Gjorgjina Cenikj, Carola Doerr, Tome Eftimov:
Generalization Ability of Feature-based Performance Prediction Models: A Statistical Analysis across Benchmarks. CoRR abs/2405.12259 (2024) - [i119]Gjorgjina Cenikj, Ana Nikolikj, Gasper Petelin, Niki van Stein, Carola Doerr, Tome Eftimov:
A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization. CoRR abs/2406.06629 (2024) - [i118]Konstantin Dietrich, Raphael Patrick Prager, Carola Doerr, Heike Trautmann:
Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization. CoRR abs/2407.07439 (2024) - [i117]François Clément, Carola Doerr, Kathrin Klamroth, Luís Paquete:
Transforming the Challenge of Constructing Low-Discrepancy Point Sets into a Permutation Selection Problem. CoRR abs/2407.11533 (2024) - [i116]Maria Laura Santoni, Elena Raponi, Aneta Neumann, Frank Neumann, Mike Preuss, Carola Doerr:
Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization. CoRR abs/2408.16393 (2024) - 2023
- [j41]Carola Doerr, Martin S. Krejca:
Run Time Analysis for Random Local Search on Generalized Majority Functions. IEEE Trans. Evol. Comput. 27(5): 1385-1397 (2023) - [j40]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) - [c125]Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer:
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization. AutoML 2023: 6/1-50 - [c124]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 - [c123]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 - [c122]Ana Nikolikj, Michal Pluhacek, Carola Doerr, Peter Korosec, Tome Eftimov:
Sensitivity Analysis of RF+clust for Leave-One-Problem-Out Performance Prediction. CEC 2023: 1-8 - [c121]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 - [c120]Ana Nikolikj, Carola Doerr, Tome Eftimov:
RF+clust for Leave-One-Problem-Out Performance Prediction. EvoApplications@EvoStar 2023: 285-301 - [c119]Carola Doerr:
Bridging Theory and Practice in Evolutionary Computation? FOGA 2023: 2 - [c118]Deyao Chen, Maxim Buzdalov, Carola Doerr, Nguyen Dang:
Using Automated Algorithm Configuration for Parameter Control. FOGA 2023: 38-49 - [c117]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 - [c116]Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer:
Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization. GECCO Companion 2023: 483-486 - [c115]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 - [c114]Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov:
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. GECCO 2023: 529-537 - [c113]Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov:
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. GECCO 2023: 813-821 - [c112]Diederick Vermetten, Furong Ye, Carola Doerr:
Using Affine Combinations of BBOB Problems for Performance Assessment. GECCO 2023: 873-881 - [c111]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 - [c110]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 - [c109]Carola Doerr, Duri Andrea Janett, Johannes Lengler:
Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions. GECCO 2023: 1565-1574 - [c108]Maria Laura Santoni, Elena Raponi, Renato De Leone, Carola Doerr:
Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60. GECCO Companion 2023: 2390-2393 - [c107]Carola Doerr:
Benchmarking Iterative Optimization Heuristics with IOHprofiler (invited paper). ITAT 2023: 1 - [d16]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 - [d15]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB - Reproducibility and Additional Data. Version 1. Zenodo, 2023 [all versions] - [d14]Diederick Vermetten, Furong Ye, Carola Doerr:
Using Affine Combinations of BBOB Problems for Performance Assessment - Code and Data. Zenodo, 2023 - [i115]Ana Nikolikj, Carola Doerr, Tome Eftimov:
RF+clust for Leave-One-Problem-Out Performance Prediction. CoRR abs/2301.09524 (2023) - [i114]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) - [i113]Deyao Chen, Maxim Buzdalov, Carola Doerr, Nguyen Dang:
Using Automated Algorithm Configuration for Parameter Control. CoRR abs/2302.12334 (2023) - [i112]Carola Doerr, Duri Andrea Janett, Johannes Lengler:
Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions. CoRR abs/2302.12338 (2023) - [i111]Maria Laura Santoni, Elena Raponi, Renato De Leone, Carola Doerr:
Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB. CoRR abs/2303.00890 (2023) - [i110]Diederick Vermetten, Furong Ye, Carola Doerr:
Using Affine Combinations of BBOB Problems for Performance Assessment. CoRR abs/2303.04573 (2023) - [i109]Ana Nikolikj, Michal Pluhacek, Carola Doerr, Peter Korosec, Tome Eftimov:
Sensitivity Analysis of RF+clust for Leave-one-problem-out Performance Prediction. CoRR abs/2305.19375 (2023) - [i108]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) - [i107]Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov:
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. CoRR abs/2306.00479 (2023) - [i106]Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer:
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization. CoRR abs/2306.04262 (2023) - [i105]Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov:
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. CoRR abs/2306.05438 (2023) - [i104]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) - [i103]François Clément, Carola Doerr, Luís Paquete:
Heuristic Approaches to Obtain Low-Discrepancy Point Sets via Subset Selection. CoRR abs/2306.15276 (2023) - [i102]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) - [i101]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) - [i100]Elena Raponi, Nathanaël Carraz Rakotonirina, Jérémy Rapin, Carola Doerr, Olivier Teytaud:
Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym. CoRR abs/2310.00077 (2023) - [i99]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) - [i98]François Clément, Carola Doerr, Kathrin Klamroth, Luís Paquete:
Constructing Optimal L∞ Star Discrepancy Sets. CoRR abs/2311.17463 (2023) - [i97]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) - 2022
- [j39]Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov:
Fixed-Target Runtime Analysis. Algorithmica 84(6): 1762-1793 (2022) - [j38]François Clément, Carola Doerr, Luís Paquete:
Star discrepancy subset selection: Problem formulation and efficient approaches for low dimensions. J. Complex. 70: 101645 (2022) - [j37]Laurent Meunier, Herilalaina Rakotoarison, Pak-Kan Wong, Baptiste Rozière, Jérémy Rapin, Olivier Teytaud, Antoine Moreau, Carola Doerr:
Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking. IEEE Trans. Evol. Comput. 26(3): 490-500 (2022) - [j36]Thomas Bäck, Carola Doerr, Bernhard Sendhoff, Thomas Stützle:
Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software. IEEE Trans. Evol. Comput. 26(6): 1202-1205 (2022) - [j35]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. IEEE Trans. Evol. Comput. 26(6): 1526-1538 (2022) - [j34]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) - [c106]Nina Bulanova, Arina Buzdalova, Carola Doerr:
Fast Re-Optimization of LeadingOnes with Frequent Changes. CEC 2022: 1-8 - [c105]Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr:
Trajectory-based Algorithm Selection with Warm-starting. CEC 2022: 1-8 - [c104]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 - [c103]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. GECCO Companion 2022: 51-52 - [c102]Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
SELECTOR: selecting a representative benchmark suite for reproducible statistical comparison. GECCO 2022: 620-629 - [c101]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 - [c100]André Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr:
Theory-inspired parameter control benchmarks for dynamic algorithm configuration. GECCO 2022: 766-775 - [c99]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 - [c98]Quentin Renau, Johann Dréo, Alain Peres, Yann Semet, Carola Doerr, Benjamin Doerr:
Automated algorithm selection for radar network configuration. GECCO 2022: 1263-1271 - [c97]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 - [c96]Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj, Fabien Teytaud, Mathurin Videau, Olivier Teytaud, Tome Eftimov, Manuel López-Ibáñez, Carola Doerr:
Improving Nevergrad's Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration. PPSN (1) 2022: 18-31 - [c95]Furong Ye, Diederick Vermetten, Carola Doerr, Thomas Bäck:
Non-elitist Selection Can Improve the Performance of Irace. PPSN (1) 2022: 32-45 - [c94]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 - [c93]Kirill A. Antonov, Elena Raponi, Hao Wang, Carola Doerr:
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. PPSN (1) 2022: 118-131 - [c92]Ana Kostovska, Carola Doerr, Saso Dzeroski, Dragi Kocev, Pance Panov, Tome Eftimov:
Explainable Model-specific Algorithm Selection for Multi-Label Classification. SSCI 2022: 39-46 - [d13]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 - [d12]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 - [d11]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 - [d10]Furong Ye, Diederick Vermetten, Carola Doerr, Thomas Bäck:
Data Sets for the study "Non-Elitist Selection Can Improve the Performance of Irace". Zenodo, 2022 - [i96]André Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr:
Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration. CoRR abs/2202.03259 (2022) - [i95]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) - [i94]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) - [i93]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) - [i92]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) - [i91]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) - [i90]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) - [i89]Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison. CoRR abs/2204.11527 (2022) - [i88]Carola Doerr, Martin S. Krejca:
Run Time Analysis for Random Local Search on Generalized Majority Functions. CoRR abs/2204.12770 (2022) - [i87]Kirill A. Antonov, Elena Raponi, Hao Wang, Carola Doerr:
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. CoRR abs/2204.13753 (2022) - [i86]Quentin Renau, Johann Dréo, Alain Peres, Yann Semet, Carola Doerr, Benjamin Doerr:
Automated Algorithm Selection for Radar Network Configuration. CoRR abs/2205.03670 (2022) - [i85]Nina Bulanova, Arina Buzdalova, Carola Doerr:
Fast Re-Optimization of LeadingOnes with Frequent Changes. CoRR abs/2209.04391 (2022) - [i84]Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj, Fabien Teytaud, Mathurin Videau, Olivier Teytaud, Tome Eftimov, Manuel López-Ibáñez, Carola Doerr:
Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration. CoRR abs/2209.04412 (2022) - [i83]Carolin Benjamins, Elena Raponi, Anja Jankovic, Koen van der Blom, Maria Laura Santoni, Marius Lindauer, Carola Doerr:
PI is back! Switching Acquisition Functions in Bayesian Optimization. CoRR abs/2211.01455 (2022) - [i82]