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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) - [c134]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 - [c133]Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov:
Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks. CEC 2024: 1-8 - [c132]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 - [c131]Carola Doerr, Diederick Vermetten, Jacob de Nobel, Thomas Bäck:
Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. GECCO Companion 2024: 791-799 - [c130]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. GECCO 2024 - [c129]Moritz Seiler, Urban Skvorc, Carola Doerr, Heike Trautmann:
Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection. LION 2024: 361-376 - [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] - [i126]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-scale Benchmarking of Metaphor-based Optimization Heuristics. CoRR abs/2402.09800 (2024) - [i125]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) - [i124]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) - [i123]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) - [i122]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) - [i121]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) - [i120]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) - [i119]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) - [i118]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) - [i117]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) - [i116]Diederick Vermetten, Jeroen Rook, Oliver Ludger Preuß, Jacob de Nobel, Carola Doerr, Manuel López-Ibáñez, Heike Trautmann, Thomas Bäck:
MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler. CoRR abs/2412.07444 (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]Carolin Benjamins, Anja Jankovic, Elena Raponi, Koen van der Blom, Marius Lindauer, Carola Doerr:
Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis. CoRR abs/2211.09678 (2022) - [i81]Ana Kostovska, Carola Doerr, Saso Dzeroski, Dragi Kocev, Pance Panov, Tome Eftimov:
Explainable Model-specific Algorithm Selection for Multi-Label Classification. CoRR abs/2211.11227 (2022) - [i80]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2211.11332 (2022) - 2021
- [j33]Benjamin Doerr, Carola Doerr, Johannes Lengler:
Self-Adjusting Mutation Rates with Provably Optimal Success Rules. Algorithmica 83(10): 3108-3147 (2021) - [j32]Nathan Buskulic, Carola Doerr:
Maximizing Drift Is Not Optimal for Solving OneMax. Evol. Comput. 29(4): 521-541 (2021) - [c91]Kirill Antonov, Maxim Buzdalov, Arina Buzdalova, Carola Doerr:
Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms. CEC 2021: 878-885 - [c90]Quentin Renau, Johann Dréo, Carola Doerr, Benjamin Doerr:
Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions. EvoApplications 2021: 17-33 - [c89]Mohamed El Yafrani, Marcella Scoczynski Ribeiro Martins, Inkyung Sung, Markus Wagner, Carola Doerr, Peter Nielsen:
MATE: A Model-Based Algorithm Tuning Engine - A Proof of Concept Towards Transparent Feature-Dependent Parameter Tuning Using Symbolic Regression. EvoCOP 2021: 51-67 - [c88]Anja Jankovic, Tome Eftimov, Carola Doerr:
Towards Feature-Based Performance Regression Using Trajectory Data. EvoApplications 2021: 601-617 - [c87]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: optimization algorithm benchmarking ontology. GECCO Companion 2021: 239-240 - [c86]Furong Ye, Carola Doerr, Thomas Bäck:
Leveraging benchmarking data for informed one-shot dynamic algorithm selection. GECCO Companion 2021: 245-246 - [c85]Maxim Buzdalov, Carola Doerr:
Optimal static mutation strength distributions for the (1 + λ) evolutionary algorithm on OneMax. GECCO 2021: 660-668 - [c84]Tome Eftimov, Anja Jankovic, Gorjan Popovski, Carola Doerr, Peter Korosec:
Personalizing performance regression models to black-box optimization problems. GECCO 2021: 669-677 - [c83]Anja Jankovic, Gorjan Popovski, Tome Eftimov, Carola Doerr:
The impact of hyper-parameter tuning for landscape-aware performance regression and algorithm selection. GECCO 2021: 687-696 - [c82]Amine Aziz-Alaoui, Carola Doerr, Johann Dréo:
Towards large scale automated algorithm design by integrating modular benchmarking frameworks. GECCO Companion 2021: 1365-1374 - [c81]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 - [d9]Amine Aziz-Alaoui, Carola Doerr, Johann Dréo:
Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks. Zenodo, 2021 - [d8]Quentin Renau, Johann Dréo, Carola Doerr, Benjamin Doerr:
Exploratory Landscape Analysis Feature Values for the 24 Noiseless BBOB Functions. Zenodo, 2021 - [d7]Diederick Vermetten, Hao Wang, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer version 0.1.6.1 + example datasets. Zenodo, 2021 - [d6]Furong Ye, Carola Doerr, Thomas Bäck:
Data Sets for the study "Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection". Zenodo, 2021 - [d5]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Data sets for the study "Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance.". Zenodo, 2021 - [i79]Carola Doerr, Luís Paquete:
Star Discrepancy Subset Selection: Problem Formulation and Efficient Approaches for Low Dimensions. CoRR abs/2101.07881 (2021) - [i78]Quentin Renau, Johann Dréo, Carola Doerr, Benjamin Doerr:
Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions. CoRR abs/2102.00736 (2021) - [i77]Maxim Buzdalov, Carola Doerr:
Optimal Static Mutation Strength Distributions for the (1+λ) Evolutionary Algorithm on OneMax. CoRR abs/2102.04944 (2021) - [i76]Anja Jankovic, Tome Eftimov, Carola Doerr:
Towards Feature-Based Performance Regression Using Trajectory Data. CoRR abs/2102.05370 (2021) - [i75]Amine Aziz-Alaoui, Carola Doerr, Johann Dréo:
Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks. CoRR abs/2102.06435 (2021) - [i74]Furong Ye, Carola Doerr, Thomas Bäck:
Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection. CoRR abs/2102.06481 (2021) - [i73]Kirill Antonov, Maxim Buzdalov, Arina Buzdalova, Carola Doerr:
Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms. CoRR abs/2102.11461 (2021) - [i72]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) - [i71]Anja Jankovic, Gorjan Popovski, Tome Eftimov, Carola Doerr:
The Impact of Hyper-Parameter Tuning for Landscape-Aware Performance Regression and Algorithm Selection. CoRR abs/2104.09272 (2021) - [i70]Tome Eftimov, Anja Jankovic, Gorjan Popovski, Carola Doerr, Peter Korosec:
Personalizing Performance Regression Models to Black-Box Optimization Problems. CoRR abs/2104.10999 (2021) - [i69]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2104.11889 (2021) - [i68]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. CoRR abs/2106.06304 (2021) - [i67]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
- [b2]Carola Doerr:
Theory of Iterative Optimization Heuristics: From Black-Box Complexity over Algorithm Design to Parameter Control. Sorbonne Université, France, 2020 - [j31]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking discrete optimization heuristics with IOHprofiler. Appl. Soft Comput. 88: 106027 (2020) - [j30]Benjamin Doerr, Carola Doerr, Jing Yang:
Optimal parameter choices via precise black-box analysis. Theor. Comput. Sci. 801: 1-34 (2020) - [c80]Benjamin Doerr, Carola Doerr, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Optimization of Chance-Constrained Submodular Functions. AAAI 2020: 1460-1467 - [c79]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 - [c78]Jakob Bossek, Carola Doerr, Pascal Kerschke:
Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB. GECCO 2020: 778-786 - [c77]Anja Jankovic, Carola Doerr:
Landscape-aware fixed-budget performance regression and algorithm selection for modular CMA-ES variants. GECCO 2020: 841-849 - [c76]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. GECCO 2020: 903-912 - [c75]Gregor Papa, Carola Doerr:
Dynamic control parameter choices in evolutionary computation: GECCO 2020 tutorial. GECCO Companion 2020: 927-956 - [c74]Hao Wang, Carola Doerr, Ofer M. Shir, Thomas Bäck:
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion 2020: 1043-1054 - [c73]Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov:
Fixed-target runtime analysis. GECCO 2020: 1295-1303 - [c72]Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann:
Evolving Sampling Strategies for One-Shot Optimization Tasks. PPSN (1) 2020: 111-124 - [c71]Quentin Renau, Carola Doerr, Johann Dréo, Benjamin Doerr:
Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy. PPSN (2) 2020: 139-153 - [c70]Laurent Meunier, Carola Doerr, Jérémy Rapin, Olivier Teytaud:
Variance Reduction for Better Sampling in Continuous Domains. PPSN (1) 2020: 154-168 - [c69]Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr:
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. PPSN (1) 2020: 169-183 - [c68]Arina Buzdalova, Carola Doerr, Anna Rodionova:
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm. PPSN (2) 2020: 485-499 - [c67]Maxim Buzdalov, Carola Doerr:
Optimal Mutation Rates for the (1+λ ) EA on OneMax. PPSN (2) 2020: 574-587 - [c66]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. PPSN (2) 2020: 699-713 - [c65]Tome Eftimov, Gorjan Popovski, Quentin Renau, Peter Korosec, Carola Doerr:
Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes. SSCI 2020: 775-782 - [p3]Carola Doerr:
Complexity Theory for Discrete Black-Box Optimization Heuristics. Theory of Evolutionary Computation 2020: 133-212 - [p2]Benjamin Doerr, Carola Doerr:
Theory of Parameter Control for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter Choices. Theory of Evolutionary Computation 2020: 271-321 - [e3]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12269, Springer 2020, ISBN 978-3-030-58111-4 [contents] - [e2]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12270, Springer 2020, ISBN 978-3-030-58114-5 [contents] - [d4]Quentin Renau, Carola Doerr, Johann Dréo, Benjamin Doerr:
Experimental Data Set for the study "Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy". Zenodo, 2020 - [d3]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
The Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm withConfigurable Crossover Probability". Version 1. Zenodo, 2020 [all versions] - [d2]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". Version 2. Zenodo, 2020 [all versions] - [d1]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". Version 3. Zenodo, 2020 [all versions] - [i66]Jakob Bossek, Carola Doerr, Pascal Kerschke:
Initial Design Strategies and their Effects on Sequential Model-Based Optimization. CoRR abs/2003.13826 (2020) - [i65]Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov:
Fixed-Target Runtime Analysis. CoRR abs/2004.09613 (2020) - [i64]Laurent Meunier, Carola Doerr, Jérémy Rapin, Olivier Teytaud:
Variance Reduction for Better Sampling in Continuous Domains. CoRR abs/2004.11687 (2020) - [i63]Mohamed El Yafrani, Marcella Scoczynski Ribeiro Martins, Inkyung Sung, Markus Wagner, Carola Doerr, Peter Nielsen:
MATE: A Model-based Algorithm Tuning Engine. CoRR abs/2004.12750 (2020) - [i62]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Benchmarking a $(μ+λ)$ Genetic Algorithm with Configurable Crossover Probability. CoRR abs/2006.05889 (2020) - [i61]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) - [i60]Anja Jankovic, Carola Doerr:
Landscape-Aware Fixed-Budget Performance Regression and Algorithm Selection for Modular CMA-ES Variants. CoRR abs/2006.09855 (2020) - [i59]Arina Buzdalova, Carola Doerr, Anna Rodionova:
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm. CoRR abs/2006.11026 (2020) - [i58]Quentin Renau, Carola Doerr, Johann Dréo, Benjamin Doerr:
Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy. CoRR abs/2006.11135 (2020) - [i57]Maxim Buzdalov, Carola Doerr:
Optimal Mutation Rates for the (1+λ) EA on OneMax. CoRR abs/2006.11457 (2020) - [i56]Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr:
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. CoRR abs/2007.00925 (2020) - [i55]Thomas Bartz-Beielstein, Carola Doerr, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, Manuel López-Ibáñez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise:
Benchmarking in Optimization: Best Practice and Open Issues. CoRR abs/2007.03488 (2020) - [i54]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. CoRR abs/2007.03953 (2020) - [i53]Tome Eftimov, Gorjan Popovski, Quentin Renau, Peter Korosec, Carola Doerr:
Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes. CoRR abs/2009.14506 (2020) - [i52]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. CoRR abs/2010.04542 (2020) - [i51]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
- [j29]Carola Doerr, Dirk Sudholt:
Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. Algorithmica 81(2): 589-592 (2019) - [j28]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Solving Problems with Unknown Solution Length at Almost No Extra Cost. Algorithmica 81(2): 703-748 (2019) - [j27]Peyman Afshani, Manindra Agrawal, Benjamin Doerr, Carola Doerr, Kasper Green Larsen, Kurt Mehlhorn:
The query complexity of a permutation-based variant of Mastermind. Discret. Appl. Math. 260: 28-50 (2019) - [c64]Furong Ye, Carola Doerr, Thomas Bäck:
Interpolating Local and Global Search by Controlling the Variance of Standard Bit Mutation. CEC 2019: 2292-2299 - [c63]Benjamin Doerr, Carola Doerr, Frank Neumann:
Fast re-optimization via structural diversity. GECCO 2019: 233-241 - [c62]Nathan Buskulic, Carola Doerr:
Maximizing drift is not optimal for solving OneMax. GECCO (Companion) 2019: 425-426 - [c61]Anna Rodionova, Kirill Antonov, Arina Buzdalova, Carola Doerr:
Offspring population size matters when comparing evolutionary algorithms with self-adjusting mutation rates. GECCO 2019: 855-863 - [c60]Nguyen Dang, Carola Doerr:
Hyper-parameter tuning for the (1 + (λ, λ)) GA. GECCO 2019: 889-897 - [c59]Carola Doerr:
Dynamic parameter choices in evolutionary computation. GECCO (Companion) 2019: 890-922 - [c58]Diederick Vermetten, Sander van Rijn, Thomas Bäck, Carola Doerr:
Online selection of CMA-ES variants. GECCO 2019: 951-959 - [c57]Johann Dréo, Carola Doerr, Yann Semet:
Coupling the design of benchmark with algorithm in landscape-aware solver design. GECCO (Companion) 2019: 1419-1420 - [c56]Benjamin Doerr, Carola Doerr, Johannes Lengler:
Self-adjusting mutation rates with provably optimal success rules. GECCO 2019: 1479-1487 - [c55]Carola Doerr, Johann Dréo, Pascal Kerschke:
Making a case for (Hyper-)parameter tuning as benchmark problems. GECCO (Companion) 2019: 1755-1764 - [c54]Borja Calvo, Ofer M. Shir, Josu Ceberio, Carola Doerr, Hao Wang, Thomas Bäck, José Antonio Lozano:
Bayesian performance analysis for black-box optimization benchmarking. GECCO (Companion) 2019: 1789-1797 - [c53]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking discrete optimization heuristics with IOHprofiler. GECCO (Companion) 2019: 1798-1806 - [c52]Ivan Ignashov, Arina Buzdalova, Maxim Buzdalov, Carola Doerr:
Illustrating the trade-off between time, quality, and success probability in heuristic search: a discussion paper. GECCO (Companion) 2019: 1807-1812 - [c51]Anja Jankovic, Carola Doerr:
Adaptive landscape analysis. GECCO (Companion) 2019: 2032-2035 - [c50]Quentin Renau, Johann Dréo, Carola Doerr, Benjamin Doerr:
Expressiveness and robustness of landscape features. GECCO (Companion) 2019: 2048-2051 - [c49]Dmitry Vinokurov, Maxim Buzdalov, Arina Buzdalova, Benjamin Doerr, Carola Doerr:
Fixed-target runtime analysis of the (1 + 1) EA with resampling. GECCO (Companion) 2019: 2068-2071 - [e1]Tobias Friedrich, Carola Doerr, Dirk V. Arnold:
Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2019, Potsdam, Germany, August 27-29, 2019. ACM 2019, ISBN 978-1-4503-6254-2 [contents] - [i50]Furong Ye, Carola Doerr, Thomas Bäck:
Interpolating Local and Global Search by Controlling the Variance of Standard Bit Mutation. CoRR abs/1901.05573 (2019) - [i49]Benjamin Doerr, Carola Doerr, Frank Neumann:
Fast Re-Optimization via Structural Diversity. CoRR abs/1902.00304 (2019) - [i48]Benjamin Doerr, Carola Doerr, Johannes Lengler:
Self-Adjusting Mutation Rates with Provably Optimal Success Rules. CoRR abs/1902.02588 (2019) - [i47]Nguyen Dang, Carola Doerr:
Hyper-Parameter Tuning for the (1+(λ, λ)) GA. CoRR abs/1904.04608 (2019) - [i46]Diederick Vermetten, Sander van Rijn, Thomas Bäck, Carola Doerr:
Online Selection of CMA-ES Variants. CoRR abs/1904.07801 (2019) - [i45]Nathan Buskulic, Carola Doerr:
Maximizing Drift is Not Optimal for Solving OneMax. CoRR abs/1904.07818 (2019) - [i44]Anna Rodionova, Kirill Antonov, Arina Buzdalova, Carola Doerr:
Offspring Population Size Matters when Comparing Evolutionary Algorithms with Self-Adjusting Mutation Rates. CoRR abs/1904.08032 (2019) - [i43]Benjamin Doerr, Carola Doerr, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Optimization of Chance-Constrained Submodular Functions. CoRR abs/1911.11451 (2019) - [i42]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) - [i41]Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr:
One-Shot Decision-Making with and without Surrogates. CoRR abs/1912.08956 (2019) - [i40]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking Discrete Optimization Heuristics with IOHprofiler. CoRR abs/1912.09237 (2019) - [i39]Carola Doerr, Carlos M. Fonseca, Tobias Friedrich, Xin Yao:
Theory of Randomized Optimization Heuristics (Dagstuhl Reports 19431). Dagstuhl Reports 9(10): 61-94 (2019) - 2018
- [j26]Carola Doerr, Johannes Lengler:
The (1+1) Elitist Black-Box Complexity of LeadingOnes. Algorithmica 80(5): 1579-1603 (2018) - [j25]Benjamin Doerr, Carola Doerr:
Optimal Static and Self-Adjusting Parameter Choices for the (1+(λ, λ)) Genetic Algorithm. Algorithmica 80(5): 1658-1709 (2018) - [j24]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Static and Self-Adjusting Mutation Strengths for Multi-valued Decision Variables. Algorithmica 80(5): 1732-1768 (2018) - [c48]Carola Doerr:
Dynamic parameter choices in evolutionary computation. GECCO (Companion) 2018: 800-830 - [c47]Carola Doerr, Markus Wagner:
Simple on-the-fly parameter selection mechanisms for two classical discrete black-box optimization benchmark problems. GECCO 2018: 943-950 - [c46]Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck:
Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones. GECCO 2018: 951-958 - [c45]Aneta Neumann, Wanru Gao, Carola Doerr, Frank Neumann, Markus Wagner:
Discrepancy-based evolutionary diversity optimization. GECCO 2018: 991-998 - [c44]Ofer M. Shir, Carola Doerr, Thomas Bäck:
Compiling a benchmarking test-suite for combinatorial black-box optimization: a position paper. GECCO (Companion) 2018: 1753-1760 - [c43]Eduardo Carvalho Pinto, Carola Doerr:
A Simple Proof for the Usefulness of Crossover in Black-Box Optimization. PPSN (2) 2018: 29-41 - [c42]Sander van Rijn, Carola Doerr, Thomas Bäck:
Towards an Adaptive CMA-ES Configurator. PPSN (1) 2018: 54-65 - [c41]Carola Doerr, Markus Wagner:
Sensitivity of Parameter Control Mechanisms with Respect to Their Initialization. PPSN (2) 2018: 360-372 - [c40]Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang:
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489 - [i38]Carola Doerr:
Complexity Theory for Discrete Black-Box Optimization Heuristics. CoRR abs/1801.02037 (2018) - [i37]Aneta Neumann, Wanru Gao, Carola Doerr, Frank Neumann, Markus Wagner:
Discrepancy-based Evolutionary Diversity Optimization. CoRR abs/1802.05448 (2018) - [i36]Carola Doerr, Markus Wagner:
On the Effectiveness of Simple Success-Based Parameter Selection Mechanisms for Two Classical Discrete Black-Box Optimization Benchmark Problems. CoRR abs/1803.01425 (2018) - [i35]Benjamin Doerr, Carola Doerr:
Theory of Parameter Control for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter Choices. CoRR abs/1804.05650 (2018) - [i34]Benjamin Doerr, Carola Doerr, Jing Yang:
Optimal Parameter Choices via Precise Black-Box Analysis. CoRR abs/1807.03403 (2018) - [i33]Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck:
Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling (1+λ) EA Variants on OneMax and LeadingOnes. CoRR abs/1808.05850 (2018) - [i32]Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, Thomas Bäck:
IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. CoRR abs/1810.05281 (2018) - [i31]Eduardo Carvalho Pinto, Carola Doerr:
Towards a More Practice-Aware Runtime Analysis of Evolutionary Algorithms. CoRR abs/1812.00493 (2018) - [i30]Peyman Afshani, Manindra Agrawal, Benjamin Doerr, Carola Doerr, Kasper Green Larsen, Kurt Mehlhorn:
The Query Complexity of a Permutation-Based Variant of Mastermind. CoRR abs/1812.08480 (2018) - 2017
- [j23]Carola Doerr, Francisco Chicano:
Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. Algorithmica 78(2): 558-560 (2017) - [j22]Carola Doerr, Johannes Lengler:
OneMax in Black-Box Models with Several Restrictions. Algorithmica 78(2): 610-640 (2017) - [j21]Carola Doerr, Johannes Lengler:
Introducing Elitist Black-Box Models: When Does Elitist Behavior Weaken the Performance of Evolutionary Algorithms? Evol. Comput. 25(4) (2017) - [c39]Carola Doerr:
Non-static parameter choices in evolutionary computation. GECCO (Companion) 2017: 736-761 - [c38]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unknown solution length problems with no asymptotically optimal run time. GECCO 2017: 1367-1374 - [i29]Carola Doerr, Christian Igel, Lothar Thiele, Xin Yao:
Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191). Dagstuhl Reports 7(5): 22-55 (2017) - 2016
- [j20]Benjamin Doerr, Carola Doerr:
The Impact of Random Initialization on the Runtime of Randomized Search Heuristics. Algorithmica 75(3): 529-553 (2016) - [j19]Benjamin Doerr, Carola Doerr, Shay Moran, Shlomo Moran:
Simple and optimal randomized fault-tolerant rumor spreading. Distributed Comput. 29(2): 89-104 (2016) - [j18]Benjamin Doerr, Carola Doerr, Reto Spöhel, Henning Thomas:
Playing Mastermind With Many Colors. J. ACM 63(5): 42:1-42:23 (2016) - [j17]Andrea Clementi, Pierluigi Crescenzi, Carola Doerr, Pierre Fraigniaud, Francesco Pasquale, Riccardo Silvestri:
Rumor spreading in random evolving graphs. Random Struct. Algorithms 48(2): 290-312 (2016) - [c37]Benjamin Doerr, Carola Doerr:
Theory for Non-Theoreticians. GECCO (Companion) 2016: 463-482 - [c36]Benjamin Doerr, Carola Doerr, Timo Kötzing:
The Right Mutation Strength for Multi-Valued Decision Variables. GECCO 2016: 1115-1122 - [c35]Benjamin Doerr, Carola Doerr, Jing Yang:
Optimal Parameter Choices via Precise Black-Box Analysis. GECCO 2016: 1123-1130 - [c34]Carola Doerr, Johannes Lengler:
The (1+1) Elitist Black-Box Complexity of LeadingOnes. GECCO 2016: 1131-1138 - [c33]Carola Doerr, Julia Handl, Emma Hart, Gabriela Ochoa, Amarda Shehu, Tea Tusar, Anya E. Vostinar, Christine Zarges, Nur Zincir-Heywood:
Women@GECCO 2016 Chairs' Welcome. GECCO (Companion) 2016: 1447-1449 - [c32]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Provably Optimal Self-adjusting Step Sizes for Multi-valued Decision Variables. PPSN 2016: 782-791 - [c31]Benjamin Doerr, Carola Doerr, Jing Yang:
k-Bit Mutation with Self-Adjusting k Outperforms Standard Bit Mutation. PPSN 2016: 824-834 - [c30]Carola Doerr, Nicolas Bredèche, Enrique Alba, Thomas Bartz-Beielstein, Dimo Brockhoff, Benjamin Doerr, Gusz Eiben, Michael G. Epitropakis, Carlos M. Fonseca, Andreia P. Guerreiro, Evert Haasdijk, Jacqueline Heinerman, Julien Hubert, Per Kristian Lehre, Luigi Malagò, Juan Julián Merelo Guervós, Julian Francis Miller, Boris Naujoks, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Patricia Ryser-Welch, Giovanni Squillero, Jörg Stork, Dirk Sudholt, Alberto Paolo Tonda, L. Darrell Whitley, Martin Zaefferer:
Tutorials at PPSN 2016. PPSN 2016: 1012-1022 - [i28]Carola Doerr, Johannes Lengler:
The (1+1) Elitist Black-Box Complexity of LeadingOnes. CoRR abs/1604.02355 (2016) - [i27]Benjamin Doerr, Carola Doerr, Timo Kötzing:
The Right Mutation Strength for Multi-Valued Decision Variables. CoRR abs/1604.03277 (2016) - 2015
- [j16]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unbiased Black-Box Complexities of Jump Functions. Evol. Comput. 23(4): 641-670 (2015) - [j15]Benjamin Doerr, Carola Doerr, Franziska Ebel:
From black-box complexity to designing new genetic algorithms. Theor. Comput. Sci. 567: 87-104 (2015) - [c29]Axel de Perthuis de Laillevault, Benjamin Doerr, Carola Doerr:
Money for Nothing: Speeding Up Evolutionary Algorithms Through Better Initialization. GECCO 2015: 815-822 - [c28]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Solving Problems with Unknown Solution Length at (Almost) No Extra Cost. GECCO 2015: 831-838 - [c27]Carola Doerr, Johannes Lengler:
Elitist Black-Box Models: Analyzing the Impact of Elitist Selection on the Performance of Evolutionary Algorithms. GECCO 2015: 839-846 - [c26]Benjamin Doerr, Carola Doerr:
Optimal Parameter Choices Through Self-Adjustment: Applying the 1/5-th Rule in Discrete Settings. GECCO 2015: 1335-1342 - [c25]Benjamin Doerr, Carola Doerr:
A Tight Runtime Analysis of the (1+(λ, λ)) Genetic Algorithm on OneMax. GECCO 2015: 1423-1430 - [c24]Carola Doerr, Johannes Lengler:
OneMax in Black-Box Models with Several Restrictions. GECCO 2015: 1431-1438 - [i26]Carola Doerr, Johannes Lengler:
OneMax in Black-Box Models with Several Restrictions. CoRR abs/1504.02644 (2015) - [i25]Benjamin Doerr, Carola Doerr:
Optimal Parameter Choices Through Self-Adjustment: Applying the 1/5-th Rule in Discrete Settings. CoRR abs/1504.03212 (2015) - [i24]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Solving Problems with Unknown Solution Length at (Almost) No Extra Cost. CoRR abs/1506.05913 (2015) - [i23]Benjamin Doerr, Carola Doerr:
A Tight Runtime Analysis of the $(1+(λ, λ))$ Genetic Algorithm on OneMax. CoRR abs/1506.05937 (2015) - [i22]Carola Doerr, Johannes Lengler:
Introducing Elitist Black-Box Models: When Does Elitist Selection Weaken the Performance of Evolutionary Algorithms? CoRR abs/1508.06802 (2015) - 2014
- [j14]Benjamin Doerr, Carola Doerr, Timo Kötzing:
The unbiased black-box complexity of partition is polynomial. Artif. Intell. 216: 275-286 (2014) - [j13]Benjamin Doerr, Carola Winzen:
Ranking-Based Black-Box Complexity. Algorithmica 68(3): 571-609 (2014) - [j12]Carola Doerr, G. Ramakrishna, Jens M. Schmidt:
Computing Minimum Cycle Bases in Weighted Partial 2-Trees in Linear Time. J. Graph Algorithms Appl. 18(3): 325-346 (2014) - [j11]Benjamin Doerr, Carola Winzen:
Playing Mastermind with Constant-Size Memory. Theory Comput. Syst. 55(4): 658-684 (2014) - [j10]Benjamin Doerr, Carola Winzen:
Reducing the arity in unbiased black-box complexity. Theor. Comput. Sci. 545: 108-121 (2014) - [j9]Xujin Chen, Benjamin Doerr, Carola Doerr, Xiaodong Hu, Weidong Ma, Rob van Stee:
The Price of Anarchy for Selfish Ring Routing is Two. ACM Trans. Economics and Comput. 2(2): 8:1-8:24 (2014) - [c23]Benjamin Doerr, Carola Doerr:
Black-box complexity: from complexity theory to playing mastermind. GECCO (Companion) 2014: 623-646 - [c22]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unbiased black-box complexities of jump functions: how to cross large plateaus. GECCO 2014: 769-776 - [c21]Benjamin Doerr, Carola Doerr:
The impact of random initialization on the runtime of randomized search heuristics. GECCO 2014: 1375-1382 - [c20]Una-May O'Reilly, Anna Esparcia-Alcázar, Anne Auger, Carola Doerr, Anikó Ekárt, Gabriela Ochoa:
Women@GECCO 2014. GECCO (Companion) 2014: 1487-1488 - [i21]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unbiased Black-Box Complexities of Jump Functions - How to Cross Large Plateaus. CoRR abs/1403.7806 (2014) - 2013
- [j8]Benjamin Doerr, Thomas Jansen, Dirk Sudholt, Carola Winzen, Christine Zarges:
Mutation Rate Matters Even When Optimizing Monotonic Functions. Evol. Comput. 21(1): 1-27 (2013) - [j7]Carola Winzen:
Direction-reversing quasi-random rumor spreading with restarts. Inf. Process. Lett. 113(22-24): 921-926 (2013) - [j6]Benjamin Doerr, Timo Kötzing, Johannes Lengler, Carola Winzen:
Black-box complexities of combinatorial problems. Theor. Comput. Sci. 471: 84-106 (2013) - [c19]Peyman Afshani, Manindra Agrawal, Benjamin Doerr, Carola Doerr, Kasper Green Larsen, Kurt Mehlhorn:
The Query Complexity of Finding a Hidden Permutation. Space-Efficient Data Structures, Streams, and Algorithms 2013: 1-11 - [c18]Andrea Clementi, Pierluigi Crescenzi, Carola Doerr, Pierre Fraigniaud, Marco Isopi, Alessandro Panconesi, Francesco Pasquale, Riccardo Silvestri:
Rumor Spreading in Random Evolving Graphs. ESA 2013: 325-336 - [c17]Benjamin Doerr, Carola Doerr:
Black-box complexity: from complexity theory to playing mastermind. GECCO (Companion) 2013: 617-640 - [c16]Benjamin Doerr, Carola Doerr, Franziska Ebel:
Lessons from the black-box: fast crossover-based genetic algorithms. GECCO 2013: 781-788 - [c15]Carola Doerr, François-Michel De Rainville:
Constructing low star discrepancy point sets with genetic algorithms. GECCO 2013: 789-796 - [c14]Benjamin Doerr, Reto Spöhel, Henning Thomas, Carola Winzen:
Playing Mastermind with Many Colors. SODA 2013: 695-704 - [c13]Carola Doerr, G. Ramakrishna, Jens M. Schmidt:
Computing Minimum Cycle Bases in Weighted Partial 2-Trees in Linear Time. WG 2013: 225-236 - [i20]Andrea Clementi, Pierluigi Crescenzi, Carola Doerr, Pierre Fraigniaud, Marco Isopi, Alessandro Panconesi, Francesco Pasquale, Riccardo Silvestri:
Rumor Spreading in Random Evolving Graphs. CoRR abs/1302.3828 (2013) - [i19]Carola Doerr, G. Ramakrishna, Jens M. Schmidt:
Computing Minimum Cycle Bases in Weighted Partial 2-Trees in Linear Time. CoRR abs/1303.0728 (2013) - [i18]Carola Doerr, François-Michel De Rainville:
Constructing Low Star Discrepancy Point Sets with Genetic Algorithms. CoRR abs/1304.1978 (2013) - [i17]Benjamin Doerr, Carola Doerr:
Collecting Coupons with Random Initial Stake. CoRR abs/1308.6384 (2013) - 2012
- [j5]Benjamin Doerr, Daniel Johannsen, Carola Winzen:
Multiplicative Drift Analysis. Algorithmica 64(4): 673-697 (2012) - [j4]Benjamin Doerr, Carola Winzen:
Memory-restricted black-box complexity of OneMax. Inf. Process. Lett. 112(1-2): 32-34 (2012) - [j3]Michael Gnewuch, Magnus Wahlström, Carola Winzen:
A New Randomized Algorithm to Approximate the Star Discrepancy Based on Threshold Accepting. SIAM J. Numer. Anal. 50(2): 781-807 (2012) - [j2]Benjamin Doerr, Daniel Johannsen, Carola Winzen:
Non-existence of linear universal drift functions. Theor. Comput. Sci. 436: 71-86 (2012) - [c12]Benjamin Doerr, Reto Spöhel, Henning Thomas, Carola Winzen:
Playing Mastermind with Many Colors. CTW 2012: 108-111 - [c11]Benjamin Doerr, Carola Winzen:
Reducing the arity in unbiased black-box complexity. GECCO 2012: 1309-1316 - [c10]Benjamin Doerr, Carola Winzen:
Playing Mastermind With Constant-Size Memory. STACS 2012: 441-452 - [c9]Xujin Chen, Benjamin Doerr, Xiaodong Hu, Weidong Ma, Rob van Stee, Carola Winzen:
The Price of Anarchy for Selfish Ring Routing Is Two. WINE 2012: 420-433 - [i16]Benjamin Doerr, Carola Winzen:
Reducing the Arity in Unbiased Black-Box Complexity. CoRR abs/1203.4111 (2012) - [i15]Benjamin Doerr, Reto Spöhel, Henning Thomas, Carola Winzen:
Playing Mastermind with Many Colors. CoRR abs/1207.0773 (2012) - [i14]Benjamin Doerr, Shay Moran, Shlomo Moran, Carola Winzen:
Fast Fault Tolerant Rumor Spreading with Minimum Message Complexity. CoRR abs/1209.6158 (2012) - [i13]Xujin Chen, Benjamin Doerr, Xiaodong Hu, Weidong Ma, Rob van Stee, Carola Winzen:
The Price of Anarchy for Selfish Ring Routing is Two. CoRR abs/1210.0230 (2012) - [i12]Benjamin Doerr, Carola Winzen:
Black-Box Complexity: Breaking the $O(n \log n)$ Barrier of LeadingOnes. CoRR abs/1210.6465 (2012) - [i11]Peyman Afshani, Manindra Agrawal, Benjamin Doerr, Carola Winzen, Kasper Green Larsen, Kurt Mehlhorn:
The Deterministic and Randomized Query Complexity of a Simple Guessing Game. Electron. Colloquium Comput. Complex. TR12 (2012) - 2011
- [b1]Carola Winzen:
Toward a complexity theory for randomized search heuristics. Universität Saarbrücken, 2011, pp. 1-171 - [c8]Benjamin Doerr, Carola Winzen:
Black-Box Complexity: Breaking the O(n logn) Barrier of LeadingOnes. Artificial Evolution 2011: 205-216 - [c7]Benjamin Doerr, Carola Winzen:
Towards a Complexity Theory of Randomized Search Heuristics: Ranking-Based Black-Box Complexity. CSR 2011: 15-28 - [c6]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen:
Faster black-box algorithms through higher arity operators. FOGA 2011: 163-172 - [c5]Benjamin Doerr, Johannes Lengler, Timo Kötzing, Carola Winzen:
Black-box complexities of combinatorial problems. GECCO 2011: 981-988 - [c4]Benjamin Doerr, Timo Kötzing, Carola Winzen:
Too fast unbiased black-box algorithms. GECCO 2011: 2043-2050 - [p1]Carola Winzen:
Entwicklung einer Komplexitätstheorie für randomisierte Suchheuristiken: Black-Box-Modelle. Ausgezeichnete Informatikdissertationen 2011: 281-290 - [i10]Benjamin Doerr, Daniel Johannsen, Carola Winzen:
Multiplicative Drift Analysis. CoRR abs/1101.0776 (2011) - [i9]Benjamin Doerr, Carola Winzen:
Towards a Complexity Theory of Randomized Search Heuristics: Ranking-Based Black-Box Complexity. CoRR abs/1102.1140 (2011) - [i8]Michael Gnewuch, Magnus Wahlström, Carola Winzen:
A Randomized Algorithm Based on Threshold Accepting to Approximate the Star Discrepancy. CoRR abs/1103.2102 (2011) - [i7]Carola Winzen:
Direction-Reversing Quasi-Random Rumor Spreading with Restarts. CoRR abs/1103.2429 (2011) - [i6]Benjamin Doerr, Timo Kötzing, Johannes Lengler, Carola Winzen:
Black-Box Complexities of Combinatorial Problems. CoRR abs/1108.0342 (2011) - [i5]Benjamin Doerr, Carola Winzen:
Playing Mastermind With Constant-Size Memory. CoRR abs/1110.3619 (2011) - [i4]Benjamin Doerr, Carola Winzen:
Memory-Restricted Black-Box Complexity. Electron. Colloquium Comput. Complex. TR11 (2011) - 2010
- [c3]Benjamin Doerr, Daniel Johannsen, Carola Winzen:
Drift analysis and linear functions revisited. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c2]Benjamin Doerr, Daniel Johannsen, Carola Winzen:
Multiplicative drift analysis. GECCO 2010: 1449-1456 - [c1]Benjamin Doerr, Thomas Jansen, Dirk Sudholt, Carola Winzen, Christine Zarges:
Optimizing Monotone Functions Can Be Difficult. PPSN (1) 2010: 42-51 - [i3]Benjamin Doerr, Thomas Jansen, Dirk Sudholt, Carola Winzen, Christine Zarges:
Optimizing Monotone Functions Can Be Difficult. CoRR abs/1010.1429 (2010) - [i2]Benjamin Doerr, Daniel Johannsen, Carola Winzen:
Non-Existence of Linear Universal Drift Functions. CoRR abs/1011.3466 (2010) - [i1]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen:
Faster Black-Box Algorithms Through Higher Arity Operators. CoRR abs/1012.0952 (2010)
2000 – 2009
- 2009
- [j1]Michael Gnewuch, Anand Srivastav, Carola Winzen:
Finding optimal volume subintervals with k points and calculating the star discrepancy are NP-hard problems. J. Complex. 25(2): 115-127 (2009)
Coauthor Index
[j44] [c131] [c130] [c128] [d19] [d18] [d17] [i126] [i123] [i116] [c124] [c111] [d15] [i104] [i97] [j36] [j35] [j34] [c104] [c103] [c99] [c97] [c95] [d11] [d10] [i95] [i93] [i91] [c86] [c81] [d7] [d6] [d5] [i74] [i72] [i68] [i67] [j31] [c79] [c76] [c74] [c66] [e3] [e2] [d3] [d2] [d1] [i62] [i61] [i54] [c64] [c58] [c54] [c53] [i50] [i46] [i42] [i40] [c46] [c44] [c42] [i33] [i32]
[j39] [c98] [i86] [j33] [c90] [d8] [i78] [j30] [c80] [c73] [c71] [p2] [d4] [i65] [i58] [j28] [j27] [c63] [c56] [c50] [c49] [i49] [i48] [i43] [j25] [j24] [i35] [i34] [i30] [c38] [j20] [j19] [j18] [c37] [c36] [c35] [c32] [c31] [c30] [i27] [j16] [j15] [c29] [c28] [c26] [c25] [i25] [i24] [i23] [j14] [j13] [j11] [j10] [j9] [c23] [c22] [c21] [i21] [j8] [j6] [c19] [c17] [c16] [c14] [i17] [j5] [j4] [j2] [c12] [c11] [c10] [c9] [i16] [i15] [i14] [i13] [i12] [i11] [c8] [c7] [c6] [c5] [c4] [i10] [i9] [i6] [i5] [i4] [c3] [c2] [c1] [i3] [i2] [i1]
[c134] [c133] [i122] [i121] [i120] [j40] [c123] [c122] [c121] [c120] [c117] [c115] [c114] [c113] [i115] [i114] [i109] [i108] [i107] [i105] [i101] [i99] [c105] [c102] [c101] [c96] [c94] [c92] [d13] [d12] [i94] [i92] [i90] [i89] [i84] [i81] [i80] [c88] [c87] [c84] [c83] [i76] [i71] [i70] [i69] [c65] [i55] [i53]
Diederick Vermetten
aka: Diederick L. Vermetten
aka: Diederick L. Vermetten
[j44] [c133] [c132] [c131] [c130] [c128] [d20] [d19] [d18] [d17] [i126] [i125] [i124] [i123] [i122] [i116] [j40] [c124] [c123] [c121] [c117] [c115] [c112] [c111] [c110] [d16] [d15] [d14] [i114] [i110] [i108] [i104] [i102] [i101] [i99] [i97] [j34] [c105] [c104] [c101] [c99] [c97] [c95] [c94] [d13] [d12] [d11] [d10] [i95] [i94] [i93] [i92] [i91] [i90] [i80] [c87] [c81] [d7] [i72] [i69] [i67] [c79] [c76] [i61] [i54] [i51] [c58] [i46] [i42]
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