Jacob de Nobel

According to our database, Jacob de Nobel authored at least 24 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Abnormal Mutations: Evolution Strategies Don't Require Gaussianity.

Jacob de Nobel, Diederick Vermetten, Hao Wang, Anna V. Kononova, Günter Rudolph, Thomas Bäck

CoRR, February, 2025

2024

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics.

Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck

Evol. Comput., 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, Heike Trautmann, Thomas Bäck

CoRR, 2024

Solving Deep Reinforcement Learning Benchmarks with Linear Policy Networks.

Annie Wong, Jacob de Nobel, Thomas Bäck, Aske Plaat, Anna V. Kononova

CoRR, 2024

Avoiding Redundant Restarts in Multimodal Global Optimization.

Jacob de Nobel, Diederick Vermetten, Anna V. Kononova, Ofer M. Shir, Thomas Bäck

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Optimizing Causal Interventions in Hybrid Bayesian Networks - A Discretization, Knowledge Compilation, and Heuristic Optimization Approach.

Maarten C. Vonk, Diederick Vermetten, Jacob de Nobel, Sebastiaan Brand, Ninoslav Malekovic, Thomas Bäck, Alfons Laarman, Anna V. Kononova

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2024

Sampling in CMA-ES: Low Numbers of Low Discrepancy Points.

Jacob de Nobel, Diederick Vermetten, Thomas H. W. Bäck, Anna V. Kononova

Proceedings of the 16th International Joint Conference on Computational Intelligence, 2024

What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms.

Furong Ye, Frank Neumann, Jacob de Nobel, Aneta Neumann, Thomas Bäck

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler.

Carola Doerr, Diederick Vermetten, Jacob de Nobel, Thomas Bäck

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem.

Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

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

Dataset, February, 2023

Evolutionary Algorithms for Parameter Optimization - Thirty Years Later.

Thomas H. W. Bäck, Anna V. Kononova, Bas van Stein, Hao Wang, Kirill A. Antonov, Roman T. Kalkreuth, Jacob de Nobel, Diederick Vermetten, Roy de Winter, Furong Ye

Evol. Comput., 2023

When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems.

André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye, Thomas Bäck, Anna V. Kononova

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler.

Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms.

François Clément, Diederick Vermetten, Jacob de Nobel, Alexandre D. Jesus, Luís Paquete, Carola Doerr

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler.

Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck

Proceedings of the IEEE Congress on Evolutionary Computation, 2023

2022

Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data.

Anja Jankovic, Ana Kostovska, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr

Dataset, April, 2022

Optimizing Stimulus Energy for Cochlear Implants with a Machine Learning Model of the Auditory Nerve.

Jacob de Nobel, Anna V. Kononova, Jeroen Briaire, Johan H. M. Frijns, Thomas Bäck

CoRR, 2022

Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features.

Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr

Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Benchmarking and analyzing iterative optimization heuristics with IOH profiler.

Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Trajectory-based Algorithm Selection with Warm-starting.

Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2021

Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants.

Jacob de Nobel, Hao Wang, Thomas Bäck

CoRR, 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, Carola Doerr, Thomas Bäck

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Explorative data analysis of time series based algorithm features of CMA-ES variants.

Jacob de Nobel, Hao Wang, Thomas Bäck

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021