( en | de | ru )

 

Disambiguation of "Doerr, Carola"

Author of the publication

copydeleteadd this publication to your clipboard
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems.

, , , , and . GECCO, page 813-821. ACM, (2023)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Guido Doerr

Joseph Doerr

Matthias Doerr

Benjamin Doerr

Karin Doerr

 

Other publications of authors with the same name

High Dimensional Bayesian Optimization Assisted by Principal Component Analysis., , , , and . PPSN (1), volume 12269 of Lecture Notes in Computer Science, page 169-183. Springer, (2020)Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy., , , and . PPSN (2), volume 12270 of Lecture Notes in Computer Science, page 139-153. Springer, (2020)k-Bit Mutation with Self-Adjusting k Outperforms Standard Bit Mutation., , and . PPSN, volume 9921 of Lecture Notes in Computer Science, page 824-834. Springer, (2016)Black-box complexity: from complexity theory to playing mastermind., and . GECCO (Companion), page 617-640. ACM, (2013)Optimal static mutation strength distributions for the (1 + λ) evolutionary algorithm on OneMax., and . GECCO, page 660-668. ACM, (2021)Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022., , , and . GECCO Companion, page 51-52. ACM, (2022)MATE: A Model-Based Algorithm Tuning Engine - A Proof of Concept Towards Transparent Feature-Dependent Parameter Tuning Using Symbolic Regression., , , , , and . EvoCOP, volume 12692 of Lecture Notes in Computer Science, page 51-67. Springer, (2021)Self-Adjusting Weighted Expected Improvement for Bayesian Optimization., , , , and . AutoML, volume 224 of Proceedings of Machine Learning Research, page 6/1-50. PMLR, (2023)Self-adjusting mutation rates with provably optimal success rules., , and . GECCO, page 1479-1487. ACM, (2019)Elitist Black-Box Models: Analyzing the Impact of Elitist Selection on the Performance of Evolutionary Algorithms., and . GECCO, page 839-846. ACM, (2015)