392 results on '"Carola Doerr"'
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2. Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection.
3. Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box Optimization.
4. Learned Features vs. Classical ELA on Affine BBOB Functions.
5. Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler.
6. Generalization Ability of Feature-Based Performance Prediction Models: A Statistical Analysis Across Benchmarks.
7. Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks.
8. Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler.
9. Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions.
10. IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics.
11. Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB.
12. Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics.
13. Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization.
14. Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms.
15. RF+clust for Leave-One-Problem-Out Performance Prediction.
16. Using Automated Algorithm Configuration for Parameter Control.
17. Sensitivity Analysis of RF+clust for Leave-One-Problem-Out Performance Prediction.
18. DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems.
19. Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances.
20. Benchmarking and analyzing iterative optimization heuristics with IOHprofiler.
21. Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms.
22. Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60.
23. Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions.
24. Comparing Algorithm Selection Approaches on Black-Box Optimization Problems.
25. Assessing the Generalizability of a Performance Predictive Model.
26. Using Affine Combinations of BBOB Problems for Performance Assessment.
27. Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization.
28. MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler.
29. Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization.
30. Transforming the Challenge of Constructing Low-Discrepancy Point Sets into a Permutation Selection Problem.
31. A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization.
32. Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms.
33. Run Time Analysis for Random Local Search on Generalized Majority Functions.
34. OPTION: OPTImization Algorithm Benchmarking ONtology.
35. Explainable Model-specific Algorithm Selection for Multi-Label Classification.
36. Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features.
37. High Dimensional Bayesian Optimization with Kernel Principal Component Analysis.
38. Non-elitist Selection Can Improve the Performance of Irace.
39. Improving Nevergrad's Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration.
40. Trajectory-based Algorithm Selection with Warm-starting.
41. Fast Re-Optimization of LeadingOnes with Frequent Changes.
42. Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms.
43. The importance of landscape features for performance prediction of modular CMA-ES variants.
44. Theory-inspired parameter control benchmarks for dynamic algorithm configuration.
45. SELECTOR: selecting a representative benchmark suite for reproducible statistical comparison.
46. Automated algorithm selection for radar network configuration.
47. Benchmarking and analyzing iterative optimization heuristics with IOH profiler.
48. Heuristic approaches to obtain low-discrepancy point sets via subset selection.
49. IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics.
50. Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking.
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