Finding optimal volume subintervals with k points and calculating the star discrepancy are NP-hard problems. - Michael Gnewuch; Anand Srivastav; Carola Winzen (J. Complex., 2009)

Drift analysis and linear functions revisited. - Benjamin Doerr; Daniel Johannsen; Carola Winzen (IEEE Congress on Evolutionary Computation, 2010)

Optimizing Monotone Functions Can Be Difficult. - Benjamin Doerr; Thomas Jansen 001; Dirk Sudholt; Carola Winzen; Christine Zarges (PPSN (1), 2010)

Toward a complexity theory for randomized search heuristics. - Carola Winzen (2011)

Black-Box Complexity: Breaking the O(n logn) Barrier of LeadingOnes. - Benjamin Doerr; Carola Winzen (Artificial Evolution, 2011)

Towards a Complexity Theory of Randomized Search Heuristics: Ranking-Based Black-Box Complexity. - Benjamin Doerr; Carola Winzen (CSR, 2011)

Faster black-box algorithms through higher arity operators. - Benjamin Doerr; Daniel Johannsen; Timo Kötzing; Per Kristian Lehre; Markus Wagner 007; Carola Winzen (FOGA, 2011)

Too fast unbiased black-box algorithms. - Benjamin Doerr; Timo Kötzing; Carola Winzen (GECCO, 2011)

Entwicklung einer Komplexitätstheorie für randomisierte Suchheuristiken: Black-Box-Modelle. - Carola Winzen (Ausgezeichnete Informatikdissertationen, 2011)

A Randomized Algorithm Based on Threshold Accepting to Approximate the Star Discrepancy - Michael Gnewuch; Magnus Wahlström; Carola Winzen (CoRR, 2011)

Memory-Restricted Black-Box Complexity. - Benjamin Doerr; Carola Winzen (Electron. Colloquium Comput. Complex., 2011)

Multiplicative Drift Analysis. - Benjamin Doerr; Daniel Johannsen; Carola Winzen (Algorithmica, 2012)

Fast Fault Tolerant Rumor Spreading with Minimum Message Complexity - Benjamin Doerr; Shay Moran; Shlomo Moran; Carola Winzen (CoRR, 2012)

Black-Box Complexity: Breaking the $O(n log n)$ Barrier of LeadingOnes - Benjamin Doerr; Carola Winzen (CoRR, 2012)

The Deterministic and Randomized Query Complexity of a Simple Guessing Game. - Peyman Afshani; Manindra Agrawal; Benjamin Doerr; Carola Winzen; Kasper Green Larsen; Kurt Mehlhorn (Electron. Colloquium Comput. Complex., 2012)

Memory-restricted black-box complexity of OneMax. - Benjamin Doerr; Carola Winzen (Inf. Process. Lett., 2012)

A New Randomized Algorithm to Approximate the Star Discrepancy Based on Threshold Accepting. - Michael Gnewuch; Magnus Wahlström; Carola Winzen (SIAM J. Numer. Anal., 2012)

Non-existence of linear universal drift functions. - Benjamin Doerr; Daniel Johannsen; Carola Winzen (Theor. Comput. Sci., 2012)

The Query Complexity of Finding a Hidden Permutation. - Peyman Afshani; Manindra Agrawal; Benjamin Doerr; Carola Doerr; Kasper Green Larsen; Kurt Mehlhorn (Space-Efficient Data Structures, Streams, and Algorithms, 2013)

Rumor Spreading in Random Evolving Graphs. - Andrea Clementi; Pierluigi Crescenzi; Carola Doerr; Pierre Fraigniaud; Marco Isopi; Alessandro Panconesi; Francesco Pasquale; Riccardo Silvestri (ESA, 2013)

Black-box complexity: from complexity theory to playing mastermind. - Benjamin Doerr; Carola Doerr (GECCO (Companion), 2013)

Lessons from the black-box: fast crossover-based genetic algorithms. - Benjamin Doerr; Carola Doerr; Franziska Ebel (GECCO, 2013)

Constructing low star discrepancy point sets with genetic algorithms. - Carola Doerr; François-Michel De Rainville (GECCO, 2013)

Collecting Coupons with Random Initial Stake. - Benjamin Doerr; Carola Doerr (CoRR, 2013)

Mutation Rate Matters Even When Optimizing Monotonic Functions. - Benjamin Doerr; Thomas Jansen 001; Dirk Sudholt; Carola Winzen; Christine Zarges (Evol. Comput., 2013)

Direction-reversing quasi-random rumor spreading with restarts. - Carola Winzen (Inf. Process. Lett., 2013)

Black-box complexities of combinatorial problems. - Benjamin Doerr; Timo Kötzing; Johannes Lengler; Carola Winzen (Theor. Comput. Sci., 2013)

Unbiased black-box complexities of jump functions: how to cross large plateaus. - Benjamin Doerr; Carola Doerr; Timo Kötzing (GECCO, 2014)

Women@GECCO 2014. - Una-May O'Reilly; Anna Esparcia-Alcázar; Anne Auger; Carola Doerr; Anikó Ekárt; Gabriela Ochoa (GECCO (Companion), 2014)

The unbiased black-box complexity of partition is polynomial. - Benjamin Doerr; Carola Doerr; Timo Kötzing (Artif. Intell., 2014)

Ranking-Based Black-Box Complexity. - Benjamin Doerr; Carola Winzen (Algorithmica, 2014)

Computing Minimum Cycle Bases in Weighted Partial 2-Trees in Linear Time. - Carola Doerr; G. Ramakrishna; Jens M. Schmidt (J. Graph Algorithms Appl., 2014)

Playing Mastermind with Constant-Size Memory. - Benjamin Doerr; Carola Winzen (Theory Comput. Syst., 2014)

Reducing the arity in unbiased black-box complexity. - Benjamin Doerr; Carola Winzen (Theor. Comput. Sci., 2014)

The Price of Anarchy for Selfish Ring Routing is Two. - Xujin Chen; Benjamin Doerr; Carola Doerr; Xiaodong Hu 001; Weidong Ma; Rob van Stee (ACM Trans. Economics and Comput., 2014)

Optimal Parameter Choices Through Self-Adjustment: Applying the 1/5-th Rule in Discrete Settings. - Benjamin Doerr; Carola Doerr (GECCO, 2015)

A Tight Runtime Analysis of the (1+(λ, λ)) Genetic Algorithm on OneMax. - Benjamin Doerr; Carola Doerr (GECCO, 2015)

Elitist Black-Box Models: Analyzing the Impact of Elitist Selection on the Performance of Evolutionary Algorithms. - Carola Doerr; Johannes Lengler (GECCO, 2015)

Money for Nothing: Speeding Up Evolutionary Algorithms Through Better Initialization. - Axel de Perthuis de Laillevault; Benjamin Doerr; Carola Doerr (GECCO, 2015)

Introducing Elitist Black-Box Models: When Does Elitist Selection Weaken the Performance of Evolutionary Algorithms? - Carola Doerr; Johannes Lengler (CoRR, 2015)

Unbiased Black-Box Complexities of Jump Functions. - Benjamin Doerr; Carola Doerr; Timo Kötzing (Evol. Comput., 2015)

From black-box complexity to designing new genetic algorithms. - Benjamin Doerr; Carola Doerr; Franziska Ebel (Theor. Comput. Sci., 2015)

Theory for Non-Theoreticians. - Benjamin Doerr; Carola Doerr (GECCO (Companion), 2016)

The Right Mutation Strength for Multi-Valued Decision Variables. - Benjamin Doerr; Carola Doerr; Timo Kötzing (GECCO, 2016)

Women@GECCO 2016 Chairs' Welcome. - Carola Doerr; Julia Handl; Emma Hart; Gabriela Ochoa; Amarda Shehu; Tea Tusar; Anya E. Vostinar; Christine Zarges; Nur Zincir-Heywood (GECCO (Companion), 2016)

Tutorials at PPSN 2016. - Carola Doerr; Nicolas Bredèche; Enrique Alba 001; Thomas Bartz-Beielstein; Dimo Brockhoff; Benjamin Doerr; Gusz Eiben; Michael G. Epitropakis; Carlos M. Fonseca; Andreia P. Guerreiro; Evert Haasdijk; Jacqueline Heinerman; et al. (PPSN, 2016)

Provably Optimal Self-adjusting Step Sizes for Multi-valued Decision Variables. - Benjamin Doerr; Carola Doerr; Timo Kötzing (PPSN, 2016)

k-Bit Mutation with Self-Adjusting k Outperforms Standard Bit Mutation. - Benjamin Doerr; Carola Doerr; Jing Yang 016 (PPSN, 2016)

The Impact of Random Initialization on the Runtime of Randomized Search Heuristics. - Benjamin Doerr; Carola Doerr (Algorithmica, 2016)

Simple and optimal randomized fault-tolerant rumor spreading. - Benjamin Doerr; Carola Doerr; Shay Moran; Shlomo Moran (Distributed Comput., 2016)

Playing Mastermind With Many Colors. - Benjamin Doerr; Carola Doerr; Reto Spöhel; Henning Thomas (J. ACM, 2016)

Rumor spreading in random evolving graphs. - Andrea Clementi; Pierluigi Crescenzi; Carola Doerr; Pierre Fraigniaud; Francesco Pasquale; Riccardo Silvestri (Random Struct. Algorithms, 2016)

Non-static parameter choices in evolutionary computation. - Carola Doerr (GECCO (Companion), 2017)

Unknown solution length problems with no asymptotically optimal run time. - Benjamin Doerr; Carola Doerr; Timo Kötzing (GECCO, 2017)

Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. - Carola Doerr; Francisco Chicano (Algorithmica, 2017)

OneMax in Black-Box Models with Several Restrictions. - Carola Doerr; Johannes Lengler (Algorithmica, 2017)

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191). - Carola Doerr; Christian Igel; Lothar Thiele; Xin Yao 001 (Dagstuhl Reports, 2017)

Introducing Elitist Black-Box Models: When Does Elitist Behavior Weaken the Performance of Evolutionary Algorithms? - Carola Doerr; Johannes Lengler (Evol. Comput., 2017)

Simple on-the-fly parameter selection mechanisms for two classical discrete black-box optimization benchmark problems. - Carola Doerr; Markus Wagner 007 (GECCO, 2018)

Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones. - Carola Doerr; Furong Ye; Sander van Rijn; Hao Wang 025; Thomas Bäck (GECCO, 2018)

Discrepancy-based evolutionary diversity optimization. - Aneta Neumann; Wanru Gao; Carola Doerr; Frank Neumann 001; Markus Wagner 007 (GECCO, 2018)

Compiling a benchmarking test-suite for combinatorial black-box optimization: a position paper. - Ofer M. Shir; Carola Doerr; Thomas Bäck (GECCO (Companion), 2018)

Sensitivity of Parameter Control Mechanisms with Respect to Their Initialization. - Carola Doerr; Markus Wagner 007 (PPSN (2), 2018)

Tutorials at PPSN 2018. - 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; et al. (PPSN (2), 2018)

A Simple Proof for the Usefulness of Crossover in Black-Box Optimization. - Eduardo Carvalho Pinto; Carola Doerr (PPSN (2), 2018)

Towards an Adaptive CMA-ES Configurator. - Sander van Rijn; Carola Doerr; Thomas Bäck (PPSN (1), 2018)

Optimal Static and Self-Adjusting Parameter Choices for the (1+(λ, λ)) Genetic Algorithm. - Benjamin Doerr; Carola Doerr (Algorithmica, 2018)

Static and Self-Adjusting Mutation Strengths for Multi-valued Decision Variables. - Benjamin Doerr; Carola Doerr; Timo Kötzing (Algorithmica, 2018)

The (1+1) Elitist Black-Box Complexity of LeadingOnes. - Carola Doerr; Johannes Lengler (Algorithmica, 2018)

Complexity Theory for Discrete Black-Box Optimization Heuristics. - Carola Doerr (CoRR, 2018)

On the Effectiveness of Simple Success-Based Parameter Selection Mechanisms for Two Classical Discrete Black-Box Optimization Benchmark Problems. - Carola Doerr; Markus Wagner 007 (CoRR, 2018)

Theory of Parameter Control for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter Choices. - Benjamin Doerr; Carola Doerr (CoRR, 2018)

IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. - Carola Doerr; Hao Wang 025; Furong Ye; Sander van Rijn; Thomas Bäck (CoRR, 2018)

Towards a More Practice-Aware Runtime Analysis of Evolutionary Algorithms. - Eduardo Carvalho Pinto; Carola Doerr (CoRR, 2018)

Interpolating Local and Global Search by Controlling the Variance of Standard Bit Mutation. - Furong Ye; Carola Doerr; Thomas Bäck (CEC, 2019)

Bayesian performance analysis for black-box optimization benchmarking. - Borja Calvo; Ofer M. Shir; Josu Ceberio; Carola Doerr; Hao Wang 025; Thomas Bäck; José Antonio Lozano 001 (GECCO (Companion), 2019)

Hyper-parameter tuning for the (1 + (λ, λ)) GA. - Nguyen Dang 001; Carola Doerr (GECCO, 2019)

Dynamic parameter choices in evolutionary computation. - Carola Doerr (GECCO (Companion), 2019)

Fast re-optimization via structural diversity. - Benjamin Doerr; Carola Doerr; Frank Neumann 001 (GECCO, 2019)

Making a case for (Hyper-)parameter tuning as benchmark problems. - Carola Doerr; Johann Dréo; Pascal Kerschke (GECCO (Companion), 2019)

Coupling the design of benchmark with algorithm in landscape-aware solver design. - Johann Dréo; Carola Doerr; Yann Semet (GECCO (Companion), 2019)

Illustrating the trade-off between time, quality, and success probability in heuristic search: a discussion paper. - Ivan Ignashov; Arina Buzdalova; Maxim Buzdalov 001; Carola Doerr (GECCO (Companion), 2019)

Adaptive landscape analysis. - Anja Jankovic 001; Carola Doerr (GECCO (Companion), 2019)

Expressiveness and robustness of landscape features. - Quentin Renau; Johann Dréo; Carola Doerr; Benjamin Doerr (GECCO (Companion), 2019)

Offspring population size matters when comparing evolutionary algorithms with self-adjusting mutation rates. - Anna Rodionova; Kirill Antonov; Arina Buzdalova; Carola Doerr (GECCO, 2019)

Online selection of CMA-ES variants. - Diederick Vermetten; Sander van Rijn; Thomas Bäck; Carola Doerr (GECCO, 2019)

Fixed-target runtime analysis of the (1 + 1) EA with resampling. - Dmitry Vinokurov; Maxim Buzdalov 001; Arina Buzdalova; Benjamin Doerr; Carola Doerr (GECCO (Companion), 2019)

Solving Problems with Unknown Solution Length at Almost No Extra Cost. - Benjamin Doerr; Carola Doerr; Timo Kötzing (Algorithmica, 2019)

Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. - Carola Doerr; Dirk Sudholt (Algorithmica, 2019)

Hyper-Parameter Tuning for the (1+(λ, λ)) GA. - Nguyen Dang 001; Carola Doerr (CoRR, 2019)

Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. - Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (CoRR, 2019)

One-Shot Decision-Making with and without Surrogates. - Jakob Bossek; Pascal Kerschke; Aneta Neumann; Frank Neumann 001; Carola Doerr (CoRR, 2019)

Theory of Randomized Optimization Heuristics (Dagstuhl Reports 19431). - Carola Doerr; Carlos M. Fonseca; Tobias Friedrich 001; Xin Yao 001 (Dagstuhl Reports, 2019)

The query complexity of a permutation-based variant of Mastermind. - Peyman Afshani; Manindra Agrawal; Benjamin Doerr; Carola Doerr; Kasper Green Larsen; Kurt Mehlhorn (Discret. Appl. Math., 2019)

Theory of Iterative Optimization Heuristics: From Black-Box Complexity over Algorithm Design to Parameter Control. - Carola Doerr (2020)

Optimization of Chance-Constrained Submodular Functions. - Benjamin Doerr; Carola Doerr; Aneta Neumann; Frank Neumann 001; Andrew M. Sutton (AAAI, 2020)

Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB. - Jakob Bossek; Carola Doerr; Pascal Kerschke (GECCO, 2020)

Landscape-aware fixed-budget performance regression and algorithm selection for modular CMA-ES variants. - Anja Jankovic 001; Carola Doerr (GECCO, 2020)

Dynamic control parameter choices in evolutionary computation: GECCO 2020 tutorial. - Gregor Papa; Carola Doerr (GECCO Companion, 2020)

Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. - Diederick Vermetten; Hao Wang 025; Thomas Bäck; Carola Doerr (GECCO, 2020)

Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. - Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (GECCO, 2020)

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. - Hao Wang 025; Carola Doerr; Ofer M. Shir; Thomas Bäck (GECCO Companion, 2020)

Evolving Sampling Strategies for One-Shot Optimization Tasks. - Jakob Bossek; Carola Doerr; Pascal Kerschke; Aneta Neumann; Frank Neumann 001 (PPSN (1), 2020)

Optimal Mutation Rates for the (1+λ ) EA on OneMax. - Maxim Buzdalov 001; Carola Doerr (PPSN (2), 2020)

Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm. - Arina Buzdalova; Carola Doerr; Anna Rodionova (PPSN (2), 2020)

Variance Reduction for Better Sampling in Continuous Domains. - Laurent Meunier; Carola Doerr; Jérémy Rapin; Olivier Teytaud (PPSN (1), 2020)

High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. - Elena Raponi; Hao Wang 025; Mariusz Bujny; Simonetta Boria; Carola Doerr (PPSN (1), 2020)

Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy. - Quentin Renau; Carola Doerr; Johann Dréo; Benjamin Doerr (PPSN (2), 2020)

Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (PPSN (2), 2020)

Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes. - Tome Eftimov; Gorjan Popovski; Quentin Renau; Peter Korosec; Carola Doerr (SSCI, 2020)

Benchmarking discrete optimization heuristics with IOHprofiler. - Carola Doerr; Furong Ye; Naama Horesh; Hao Wang 025; Ofer M. Shir; Thomas Bäck (Appl. Soft Comput., 2020)

Initial Design Strategies and their Effects on Sequential Model-Based Optimization. - Jakob Bossek; Carola Doerr; Pascal Kerschke (CoRR, 2020)

MATE: A Model-based Algorithm Tuning Engine. - Mohamed El Yafrani; Marcella Scoczynski Ribeiro Martins; Inkyung Sung; Markus Wagner 007; Carola Doerr; Peter Nielsen (CoRR, 2020)

Benchmarking in Optimization: Best Practice and Open Issues. - Thomas Bartz-Beielstein; Carola Doerr; Jakob Bossek; Sowmya Chandrasekaran; Tome Eftimov; Andreas Fischbach; Pascal Kerschke; Manuel López-Ibáñez 001; Katherine M. Malan; Jason H. Moore; Boris Naujoks; Patryk Orzechowski; et al. (CoRR, 2020)

IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. - Hao Wang 025; Diederick Vermetten; Furong Ye; Carola Doerr; Thomas Bäck (CoRR, 2020)

Squirrel: A Switching Hyperparameter Optimizer. - Noor H. Awad; Gresa Shala; Difan Deng; Neeratyoy Mallik; Matthias Feurer; Katharina Eggensperger; André Biedenkapp; Diederick Vermetten; Hao Wang 025; Carola Doerr; Marius Lindauer; Frank Hutter (CoRR, 2020)

Optimal parameter choices via precise black-box analysis. - Benjamin Doerr; Carola Doerr; Jing Yang 016 (Theor. Comput. Sci., 2020)

Complexity Theory for Discrete Black-Box Optimization Heuristics. - Carola Doerr (Theory of Evolutionary Computation, 2020)

Theory of Parameter Control for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter Choices. - Benjamin Doerr; Carola Doerr (Theory of Evolutionary Computation, 2020)

The Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm withConfigurable Crossover Probability". - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (Zenodo, 2020)

Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (Zenodo, 2020)

Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (Zenodo, 2020)

Experimental Data Set for the study "Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy". - Quentin Renau; Carola Doerr; Johann Dréo; Benjamin Doerr (Zenodo, 2020)

Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms. - Kirill Antonov; Maxim Buzdalov 001; Arina Buzdalova; Carola Doerr (CEC, 2021)

Towards Feature-Based Performance Regression Using Trajectory Data. - Anja Jankovic 001; Tome Eftimov; Carola Doerr (EvoApplications, 2021)

Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions. - Quentin Renau; Johann Dréo; Carola Doerr; Benjamin Doerr (EvoApplications, 2021)

MATE: A Model-Based Algorithm Tuning Engine - A Proof of Concept Towards Transparent Feature-Dependent Parameter Tuning Using Symbolic Regression. - Mohamed El Yafrani; Marcella Scoczynski Ribeiro Martins; Inkyung Sung; Markus Wagner 007; Carola Doerr; Peter Nielsen (EvoCOP, 2021)

Towards large scale automated algorithm design by integrating modular benchmarking frameworks. - Amine Aziz-Alaoui; Carola Doerr; Johann Dréo (GECCO Companion, 2021)

Optimal static mutation strength distributions for the (1 + λ) evolutionary algorithm on OneMax. - Maxim Buzdalov 001; Carola Doerr (GECCO, 2021)

Personalizing performance regression models to black-box optimization problems. - Tome Eftimov; Anja Jankovic 001; Gorjan Popovski; Carola Doerr; Peter Korosec (GECCO, 2021)

The impact of hyper-parameter tuning for landscape-aware performance regression and algorithm selection. - Anja Jankovic 001; Gorjan Popovski; Tome Eftimov; Carola Doerr (GECCO, 2021)

Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. - Jacob de Nobel; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (GECCO Companion, 2021)

Leveraging benchmarking data for informed one-shot dynamic algorithm selection. - Furong Ye; Carola Doerr; Thomas Bäck (GECCO Companion, 2021)

Self-Adjusting Mutation Rates with Provably Optimal Success Rules. - Benjamin Doerr; Carola Doerr; Johannes Lengler (Algorithmica, 2021)

Star Discrepancy Subset Selection: Problem Formulation and Efficient Approaches for Low Dimensions. - Carola Doerr; Luís Paquete (CoRR, 2021)

Optimal Static Mutation Strength Distributions for the (1+λ) Evolutionary Algorithm on OneMax. - Maxim Buzdalov 001; Carola Doerr (CoRR, 2021)

Maximizing Drift Is Not Optimal for Solving OneMax. - Nathan Buskulic; Carola Doerr (Evol. Comput., 2021)

Exploratory Landscape Analysis Feature Values for the 24 Noiseless BBOB Functions. - Quentin Renau; Johann Dréo; Carola Doerr; Benjamin Doerr (Zenodo, 2021)

Data Sets for the study "Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection". - Furong Ye; Carola Doerr; Thomas Bäck (Zenodo, 2021)

Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks. - Amine Aziz-Alaoui; Carola Doerr; Johann Dréo (Zenodo, 2021)

Data sets for the study "Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance.". - Furong Ye; Carola Doerr; Hao Wang 025; Thomas Bäck (Zenodo, 2021)

IOHanalyzer version 0.1.6.1 + example datasets. - Diederick Vermetten; Hao Wang 025; Furong Ye; Carola Doerr; Thomas Bäck (Zenodo, 2021)

Fast Re-Optimization of LeadingOnes with Frequent Changes. - Nina Bulanova; Arina Buzdalova; Carola Doerr (CEC, 2022)

Trajectory-based Algorithm Selection with Warm-starting. - Anja Jankovic 001; Diederick Vermetten; Ana Kostovska; Jacob de Nobel; Tome Eftimov; Carola Doerr (CEC, 2022)

Theory-inspired parameter control benchmarks for dynamic algorithm configuration. - André Biedenkapp; Nguyen Dang 001; Martin S. Krejca; Frank Hutter; Carola Doerr (GECCO, 2022)

SELECTOR: selecting a representative benchmark suite for reproducible statistical comparison. - Gjorgjina Cenikj; Ryan Dieter Lang; Andries Petrus Engelbrecht; Carola Doerr; Peter Korosec; Tome Eftimov (GECCO, 2022)

Benchmarking and analyzing iterative optimization heuristics with IOH profiler. - Carola Doerr; Hao Wang 025; Diederick Vermetten; Thomas Bäck; Jacob de Nobel; Furong Ye (GECCO Companion, 2022)

The importance of landscape features for performance prediction of modular CMA-ES variants. - Ana Kostovska; Diederick Vermetten; Saso Dzeroski; Carola Doerr; Peter Korosec; Tome Eftimov (GECCO, 2022)

Automated algorithm selection for radar network configuration. - Quentin Renau; Johann Dréo; Alain Peres; Yann Semet; Carola Doerr; Benjamin Doerr (GECCO, 2022)

Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms. - Diederick Vermetten; Hao Wang 025; Manuel López-Ibáñez 001; Carola Doerr; Thomas Bäck (GECCO, 2022)

IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. - Hao Wang 025; Diederick Vermetten; Furong Ye; Carola Doerr; Thomas Bäck (GECCO Companion, 2022)

Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. - Furong Ye; Carola Doerr; Hao Wang 025; Thomas Bäck (GECCO Companion, 2022)

High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. - Kirill A. Antonov; Elena Raponi; Hao Wang 025; Carola Doerr (PPSN (1), 2022)

Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. - Ana Kostovska; Anja Jankovic 001; Diederick Vermetten; Jacob de Nobel; Hao Wang 025; Tome Eftimov; Carola Doerr (PPSN (1), 2022)

Improving Nevergrad's Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration. - Risto Trajanov; Ana Nikolikj; Gjorgjina Cenikj; Fabien Teytaud; Mathurin Videau; Olivier Teytaud; Tome Eftimov; Manuel López-Ibáñez 001; Carola Doerr (PPSN (1), 2022)

Non-elitist Selection Can Improve the Performance of Irace. - Furong Ye; Diederick Vermetten; Carola Doerr; Thomas Bäck (PPSN (1), 2022)

Explainable Model-specific Algorithm Selection for Multi-Label Classification. - Ana Kostovska; Carola Doerr; Saso Dzeroski; Dragi Kocev; Pance Panov; Tome Eftimov (SSCI, 2022)

Fixed-Target Runtime Analysis. - Maxim Buzdalov 001; Benjamin Doerr; Carola Doerr; Dmitry Vinokurov (Algorithmica, 2022)

Non-Elitist Selection among Survivor Configurations can Improve the Performance of Irace. - Furong Ye; Diederick L. Vermetten; Carola Doerr; Thomas Bäck (CoRR, 2022)

Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points. - Dominik Schröder; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (CoRR, 2022)

PI is back! Switching Acquisition Functions in Bayesian Optimization. - Carolin Benjamins; Elena Raponi; Anja Jankovic 001; Koen van der Blom; Maria Laura Santoni; Marius Lindauer; Carola Doerr (CoRR, 2022)

Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis. - Carolin Benjamins; Anja Jankovic 001; Elena Raponi; Koen van der Blom; Marius Lindauer; Carola Doerr (CoRR, 2022)

Star discrepancy subset selection: Problem formulation and efficient approaches for low dimensions. - François Clément; Carola Doerr; Luís Paquete (J. Complex., 2022)

Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software. - Thomas Bäck; Carola Doerr; Bernhard Sendhoff; Thomas Stützle (IEEE Trans. Evol. Comput., 2022)

Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking. - Laurent Meunier; Herilalaina Rakotoarison; Pak-Kan Wong; Baptiste Rozière; Jérémy Rapin; Olivier Teytaud; Antoine Moreau; Carola Doerr (IEEE Trans. Evol. Comput., 2022)

Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. - Furong Ye; Carola Doerr; Hao Wang 025; Thomas Bäck (IEEE Trans. Evol. Comput., 2022)

IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics. - Hao Wang 025; Diederick Vermetten; Furong Ye; Carola Doerr; Thomas Bäck (ACM Trans. Evol. Learn. Optim., 2022)

Analyzing the Impact of Undersampling on the Benchmarkingand Configuration of Evolutionary Algorithms - Dataset. - Diederick Vermetten; Hao Wang 025; Manuel López-Ibáñez 001; Carola Doerr; Thomas Bäck (Zenodo, 2022)

Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules - Data. - Ana Kostovska; Diederick Vermetten; Saso Dzeroski; Carola Doerr; Peter Korosec; Tome Eftimov (Zenodo, 2022)

Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data. - Anja Jankovic 001; Ana Kostovska; Diederick Vermetten; Jacob de Nobel; Hao Wang 025; Tome Eftimov; Carola Doerr (Zenodo, 2022)

Data Sets for the study "Non-Elitist Selection Can Improve the Performance of Irace". - Furong Ye; Diederick Vermetten; Carola Doerr; Thomas Bäck (Zenodo, 2022)

Self-Adjusting Weighted Expected Improvement for Bayesian Optimization. - Carolin Benjamins; Elena Raponi; Anja Jankovic 001; Carola Doerr; Marius Lindauer (AutoML, 2023)

PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization. - Ana Kostovska; Gjorgjina Cenikj; Diederick Vermetten; Anja Jankovic 001; Ana Nikolikj; Urban Skvorc; Peter Korosec; Carola Doerr; Tome Eftimov (AutoML, 2023)

MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts. - Diederick Vermetten; Furong Ye; Thomas Bäck; Carola Doerr (AutoML, 2023)

Sensitivity Analysis of RF+clust for Leave-One-Problem-Out Performance Prediction. - Ana Nikolikj; Michal Pluhacek; Carola Doerr; Peter Korosec; Tome Eftimov (CEC, 2023)

Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms. - Ana Kostovska; Diederick Vermetten; Saso Dzeroski; Pance Panov; Tome Eftimov; Carola Doerr (EvoApplications@EvoStar, 2023)

RF+clust for Leave-One-Problem-Out Performance Prediction. - Ana Nikolikj; Carola Doerr; Tome Eftimov (EvoApplications@EvoStar, 2023)

Using Automated Algorithm Configuration for Parameter Control. - Deyao Chen; Maxim Buzdalov 001; Carola Doerr; Nguyen Dang 001 (FOGA, 2023)

Bridging Theory and Practice in Evolutionary Computation? - Carola Doerr (FOGA, 2023)

Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization. - Carolin Benjamins; Elena Raponi; Anja Jankovic 001; Carola Doerr; Marius Lindauer (GECCO Companion, 2023)

DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. - Gjorgjina Cenikj; Gasper Petelin; Carola Doerr; Peter Korosec; Tome Eftimov (GECCO, 2023)

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. - François Clément; Diederick Vermetten; Jacob de Nobel; Alexandre D. Jesus; Luís Paquete; Carola Doerr (GECCO, 2023)

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. - Carola Doerr; Hao Wang 025; Diederick Vermetten; Thomas Bäck; Jacob de Nobel; Furong Ye (GECCO Companion, 2023)

Comparing Algorithm Selection Approaches on Black-Box Optimization Problems. - Ana Kostovska; Anja Jankovic 001; Diederick Vermetten; Saso Dzeroski; Tome Eftimov; Carola Doerr (GECCO Companion, 2023)

Assessing the Generalizability of a Performance Predictive Model. - Ana Nikolikj; Gjorgjina Cenikj; Gordana Ispirova; Diederick Vermetten; Ryan Dieter Lang; Andries Petrus Engelbrecht; Carola Doerr; Peter Korosec; Tome Eftimov (GECCO Companion, 2023)

Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. - Ana Nikolikj; Saso Dzeroski; Mario Andrés Muñoz; Carola Doerr; Peter Korosec; Tome Eftimov (GECCO, 2023)

Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60. - Maria Laura Santoni; Elena Raponi; Renato De Leone; Carola Doerr (GECCO Companion, 2023)

Using Affine Combinations of BBOB Problems for Performance Assessment. - Diederick Vermetten; Furong Ye; Carola Doerr (GECCO, 2023)

Benchmarking Iterative Optimization Heuristics with IOHprofiler (invited paper). - Carola Doerr (ITAT, 2023)

Constructing Optimal L∞ Star Discrepancy Sets. - François Clément; Carola Doerr; Kathrin Klamroth; Luís Paquete (CoRR, 2023)

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms - Code and Data. - François Clément; Diederick Vermetten; Jacob de Nobel; Alexandre D. Jesus; Luís Paquete; Carola Doerr (Zenodo, 2023)

Using Affine Combinations of BBOB Problems for Performance Assessment - Code and Data. - Diederick Vermetten; Furong Ye; Carola Doerr (Zenodo, 2023)

Run Time Analysis for Random Local Search on Generalized Majority Functions. - Carola Doerr; Martin S. Krejca (IEEE Trans. Evol. Comput., 2023)

MA-BBOB - Reproducibility and Additional Data. - Diederick Vermetten; Furong Ye; Thomas Bäck; Carola Doerr (Zenodo, 2023)

OPTION: OPTImization Algorithm Benchmarking ONtology. - Ana Kostovska; Diederick Vermetten; Carola Doerr; Saso Dzeroski; Pance Panov; Tome Eftimov (IEEE Trans. Evol. Comput., 2023)

Generalization Ability of Feature-Based Performance Prediction Models: A Statistical Analysis Across Benchmarks. - Ana Nikolikj; Ana Kostovska; Gjorgjina Cenikj; Carola Doerr; Tome Eftimov (CEC, 2024)

Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks. - Ana Nikolikj; Ana Kostovska; Diederick Vermetten; Carola Doerr; Tome Eftimov (CEC, 2024)

Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization. - Konstantin Dietrich; Diederick Vermetten; Carola Doerr; Pascal Kerschke (GECCO, 2024)

Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. - Carola Doerr; Diederick Vermetten; Jacob de Nobel; Thomas Bäck (GECCO Companion, 2024)

Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. - Diederick Vermetten; Carola Doerr; Hao Wang 025; Anna V. Kononova; Thomas Bäck (GECCO, 2024)

Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection. - Moritz Seiler; Urban Skvorc; Carola Doerr; Heike Trautmann (LION, 2024)

Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box Optimization. - Konstantin Dietrich; Raphael Patrick Prager; Carola Doerr; Heike Trautmann (PPSN (2), 2024)

Learned Features vs. Classical ELA on Affine BBOB Functions. - Moritz Seiler; Urban Skvorc; Gjorgjina Cenikj; Carola Doerr; Heike Trautmann (PPSN (2), 2024)

Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler. - Diederick Vermetten; Johannes Lengler; Dimitri Rusin; Thomas Bäck; Carola Doerr (PPSN (2), 2024)

Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms. - Manuel López-Ibáñez 001; Diederick Vermetten; Johann Dréo; Carola Doerr (CoRR, 2024)

A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization. - Gjorgjina Cenikj; Ana Nikolikj; Gasper Petelin; Niki van Stein; Carola Doerr; Tome Eftimov (CoRR, 2024)

Transforming the Challenge of Constructing Low-Discrepancy Point Sets into a Permutation Selection Problem. - François Clément; Carola Doerr; Kathrin Klamroth; Luís Paquete (CoRR, 2024)

Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization. - Maria Laura Santoni; Elena Raponi; Aneta Neumann; Frank Neumann 001; Mike Preuss; Carola Doerr (CoRR, 2024)

MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler. - Diederick Vermetten; Jeroen Rook; Oliver Ludger Preuß; Jacob de Nobel; Carola Doerr; Manuel López-Ibáñez 001; Heike Trautmann; Thomas Bäck (CoRR, 2024)

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. - Jacob de Nobel; Furong Ye; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (Evol. Comput., 2024)

Heuristic approaches to obtain low-discrepancy point sets via subset selection. - François Clément; Carola Doerr; Luís Paquete (J. Complex., 2024)

Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics - Reproducibility Files. - Diederick Vermetten; Carola Doerr; Hao Wang 025; Anna V. Kononova; Thomas Bäck (Zenodo, 2024)

Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization - Reproducibility Files. - Konstantin Dietrich; Diederick Vermetten; Carola Doerr; Pascal Kerschke (Zenodo, 2024)

Benchmarking Dynamic Binary Value Problems with IOHprofiler - Reproducibility files. - Diederick Vermetten; Johannes Lengler; Dimitri Rusin; Thomas Bäck; Carola Doerr (Zenodo, 2024)

MA-BBOB - Reproducibility and Additional Data. - Diederick Vermetten; Furong Ye; Thomas Bäck; Carola Doerr (Zenodo, 2024)

MA-BBOB - Reproducibility and Additional Data. - Diederick Vermetten; Furong Ye; Thomas Bäck; Carola Doerr (Zenodo, 2024)

Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB. - Maria Laura Santoni; Elena Raponi; Renato De Leone; Carola Doerr (ACM Trans. Evol. Learn. Optim., 2024)

Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions. - Carola Doerr; Duri Andrea Janett; Johannes Lengler (Algorithmica, 2024)

MO-IOHinspector: Anytime Benchmarking of Multi-objective Algorithms Using IOHprofiler. - Diederick Vermetten; Jeroen Rook; Oliver L. Preuß; Jacob de Nobel; Carola Doerr; Manuel López-Ibáñez 001; Heike Trautmann; Thomas Bäck (EMO (1), 2025)

On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(λ, λ))-GA. - Tai Nguyen 008; Phong Le; André Biedenkapp; Carola Doerr; Nguyen Dang 001 (GECCO, 2025)

MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts. - Diederick Vermetten; Furong Ye; Thomas Bäck; Carola Doerr (ACM Trans. Evol. Learn. Optim., 2025)

Cascading CMA-ES Instances for Generating Input-diverse Solution Batches. - Maria Laura Santoni; Christoph Dürr; Carola Doerr; Mike Preuss; Elena Raponi (CoRR, 2025)

Optimizing With Low Budgets: A Comparison on the Black-Box Optimization Benchmarking Suite and OpenAI Gym. - Elena Raponi; Nathanaël Carraz Rakotonirina; Jérémy Rapin; Carola Doerr; Olivier Teytaud (IEEE Trans. Evol. Comput., 2025)

Multi-parameter Control for the (1+(λ,λ))-GA on OneMax via Deep Reinforcement Learning. - Tai Nguyen 008; Phong Le; Carola Doerr; Nguyen Dang 001 (CoRR, 2025)

carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks. - Carolin Benjamins; Helena Graf; Sarah Segel; Difan Deng; Tim Ruhkopf; Leona Hennig; Soham Basu; Neeratyoy Mallik; Edward Bergman; Deyao Chen; François Clément; Matthias Feurer; et al. (CoRR, 2025)

Geometric Learning in Black-Box Optimization: A GNN Framework for Algorithm Performance Prediction. - Ana Kostovska; Carola Doerr; Saso Dzeroski; Pance Panov; Tome Eftimov (CoRR, 2025)

Enhancing Parameter Control Policies with State Information. - Gianluca Covini; Denis Antipov; Carola Doerr (CoRR, 2025)