Jacob de Nobel

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 26

Top Topics

Iterative Optimization

Machine Learning

Chance Constraints

Top Venues

GECCO Companion

Publications

Furong Ye, Frank Neumann, Jacob de Nobel, Aneta Neumann, Thomas Bäck
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. GECCO (2024)
Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. GECCO (2024)
Jacob de Nobel, Diederick Vermetten, Anna V. Kononova, Ofer M. Shir, Thomas Bäck
Avoiding Redundant Restarts in Multimodal Global Optimization. CoRR (2024)
Carola Doerr, Diederick Vermetten, Jacob de Nobel, Thomas Bäck
Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. GECCO Companion (2024)
Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. CoRR (2024)
Annie Wong, Jacob de Nobel, Thomas Bäck, Aske Plaat, Anna V. Kononova
Solving Deep Reinforcement Learning Benchmarks with Linear Policy Networks. CoRR (2024)
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
Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. Evol. Comput. 31 (2) (2023)
François Clément, Diederick Vermetten, Jacob de Nobel, Alexandre D. Jesus, Luís Paquete, Carola Doerr
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. CoRR (2023)
Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CEC (2023)
André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye, Thomas Bäck, Anna V. Kononova
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. CoRR (2023)
Furong Ye, Frank Neumann, Jacob de Nobel, Aneta Neumann, Thomas Bäck
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. CoRR (2023)
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)
André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye, Thomas Bäck, Anna V. Kononova
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. GECCO (2023)
Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion (2023)
Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CoRR (2023)
Jacob de Nobel, Anna V. Kononova, Jeroen Briaire, Johan H. M. Frijns, Thomas Bäck
Optimizing Stimulus Energy for Cochlear Implants with a Machine Learning Model of the Auditory Nerve. CoRR (2022)
Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr
Trajectory-based Algorithm Selection with Warm-starting. CEC (2022)
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)
Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr
Trajectory-based Algorithm Selection with Warm-starting. CoRR (2022)
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)
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 (2022)
Jacob de Nobel, Hao Wang, Thomas Bäck
Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants. CoRR (2021)
Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. CoRR (2021)
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)
Jacob de Nobel, Hao Wang, Thomas Bäck
Explorative data analysis of time series based algorithm features of CMA-ES variants. GECCO (2021)
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 (2021)