Niki van Stein

According to our database, Niki van Stein authored at least 77 papers between 2015 and 2024.

Collaborative distances:

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

2024

Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization.

Fu Xing Long, Bas van Stein, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck

ACM Trans. Evol. Learn. Optim., June, 2024

Parallel multi-objective optimization for expensive and inexpensive objectives and constraints.

Roy de Winter, Bas Milatz, Julian Blank, Niki van Stein, Thomas Bäck, Kalyanmoy Deb

Swarm Evol. Comput., 2024

EconoJax: A Fast & Scalable Economic Simulation in Jax.

Koen Ponse, Aske Plaat, Niki van Stein, Thomas M. Moerland

CoRR, 2024

In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics.

Niki van Stein, Diederick Vermetten, Thomas Bäck

CoRR, 2024

Selection of Filters for Photonic Crystal Spectrometer Using Domain-Aware Evolutionary Algorithms.

Kirill A. Antonov, Marijn Siemons, Niki van Stein, Thomas H. W. Bäck, Ralf Kohlhaas, Anna V. Kononova

CoRR, 2024

Reasoning with Large Language Models, a Survey.

Aske Plaat, Annie Wong, Suzan Verberne, Joost Broekens, Niki van Stein, Thomas Bäck

CoRR, 2024

Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems.

Ryan Zhou, Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Martin Fyvie, Giovanni Iacca, John A. W. McCall, Niki van Stein, David Walker, Ting Hu

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

LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics.

Niki van Stein, Thomas Bäck

CoRR, 2024

Automated Federated Learning via Informed Pruning.

Christian Internò, Elena Raponi, Niki van Stein, Thomas Bäck, Markus Olhofer, Yaochu Jin, Barbara Hammer

CoRR, 2024

Shapelet-based Model-agnostic Counterfactual Local Explanations for Time Series Classification.

Qi Huang, Wei Chen, Thomas Bäck, Niki van Stein

CoRR, 2024

Explainable Benchmarking for Iterative Optimization Heuristics.

Niki van Stein, Diederick Vermetten, Anna V. Kononova, Thomas Bäck

CoRR, 2024

Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI.

Qi Huang, Emanuele Mezzi, Osman Mutlu, Miltiadis Kofinas, Vidya Prasad, Shadnan Azwad Khan, Elena Ranguelova, Niki van Stein

Proceedings of the Explainable Artificial Intelligence, 2024

A Deep Dive Into Effects of Structural Bias on CMA-ES Performance Along Affine Trajectories.

Niki van Stein, Sarah L. Thomson, Anna V. Kononova

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

Landscape-Aware Automated Algorithm Configuration Using Multi-output Mixed Regression and Classification.

Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck, Niki van Stein

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

Towards Fairness in Machine Learning: Balancing Racially Imbalanced Datasets Through Data Augmentation and Generative AI.

Anthonie Schaap, Sofoklis Kitharidis, Niki van Stein

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

Hot off the Press: Parallel Multi-Objective Optimization for Expensive and Inexpensive Objectives and Constraints.

Roy de Winter, Bas Milatz, Julian Blank, Niki van Stein, Thomas Bäck, Kalyanmoy Deb

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems.

Roy de Winter, Thomas Bäck, Niki van Stein

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

A Corridor Model Evolutionary Algorithm for Fast Converging Green Vehicle Routing Problem.

Ananta Shahane, Niki van Stein, Yingjie Fan

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

A Critical Analysis of Raven Roost Optimization.

Martijn Halsema, Diederick Vermetten, Thomas Bäck, Niki van Stein

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

A Functional Analysis Approach to Symbolic Regression.

Kirill Antonov, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein, Anna V. Kononova

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification.

Qi Huang, Sofoklis Kitharidis, Thomas Bäck, Niki van Stein

Proceedings of the 1st International Conference on Explainable AI for Neural and Symbolic Methods, 2024

2023

Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files.

Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein

Dataset, May, 2023

Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection.

Alexander Zeiser, Bekir Özcan, Bas van Stein, Thomas Bäck

Comput. Ind., April, 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

Representation-agnostic distance-driven perturbation for optimizing ill-conditioned problems.

Kirill Antonov, Anna V. Kononova, Thomas Bäck, Niki van Stein

CoRR, 2023

A data-centric approach to anomaly detection in layer-based additive manufacturing.

Alexander Zeiser, Bekir Özcan, Christoph Kracke, Bas van Stein, Thomas Bäck

Autom., 2023

The Opaque Nature of Intelligence and the Pursuit of Explainable AI.

Sarah L. Thomson, Niki van Stein, Daan van den Berg, Cees van Leeuwen

Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Challenges of ELA-Guided Function Evolution Using Genetic Programming.

Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein

Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Clustering-based Domain-Incremental Learning.

Christiaan Lamers, René Vidal, Nabil Belbachir, Niki van Stein, Thomas Bäck, Paris Giampouras

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Deep BIAS: Detecting Structural Bias using Explainable AI.

Bas van Stein, Diederick Vermetten, Fabio Caraffini, Anna V. Kononova

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

DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis.

Bas van Stein, Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck

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

Curing ill-Conditionality via Representation-Agnostic Distance-Driven Perturbations.

Kirill A. Antonov, Anna V. Kononova, Thomas Bäck, Niki van Stein

Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances.

Fu Xing Long, Diederick Vermetten, Bas van Stein, Anna V. Kononova

Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023

2022

GSAreport: Easy to Use Global Sensitivity Reporting.

Bas van Stein, Elena Raponi

J. Open Source Softw., October, 2022

Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines.

Marios Kefalas, Juan de Santiago Rojo Jr., Asteris Apostolidis, Dirk van den Herik, Bas van Stein, Thomas Bäck

J. Aerosp. Inf. Syst., June, 2022

BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain.

Diederick Vermetten, Bas van Stein, Fabio Caraffini, Leandro L. Minku, Anna V. Kononova

IEEE Trans. Evol. Comput., 2022

Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation.

Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

IEEE Trans. Evol. Comput., 2022

Constrained Multi-Objective Optimization with a Limited Budget of Function Evaluations.

Roy de Winter, Philip Bronkhorst, Bas van Stein, Thomas Bäck

Memetic Comput., 2022

Deep Learning based pipeline for anomaly detection and quality enhancement in industrial binder jetting processes.

Alexander Zeiser, Bas van Stein, Thomas Bäck

CoRR, 2022

A Comparison of Global Sensitivity Analysis Methods for Explainable AI With an Application in Genomic Prediction.

Bas van Stein, Elena Raponi, Zahra Sadeghi, Niek Bouman, Roeland C. H. J. van Ham, Thomas Bäck

IEEE Access, 2022

Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems.

Qi Huang, Roy de Winter, Bas van Stein, Thomas Bäck, Anna V. Kononova

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Multi-point acquisition function for constraint parallel efficient multi-objective optimization.

Roy de Winter, Bas van Stein, Thomas Bäck

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

Using structural bias to analyse the behaviour of modular CMA-ES.

Diederick Vermetten, Fabio Caraffini, Bas van Stein, Anna V. Kononova

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

Learning the characteristics of engineering optimization problems with applications in automotive crash.

Fu Xing Long, Bas van Stein, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck

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

2021

Exploiting Generative Models for Performance Predictions of 3D Car Designs.

Sneha Saha, Thiago Rios, Leandro L. Minku, Bas van Stein, Patricia Wollstadt, Xin Yao, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images.

Koen Ponse, Anna V. Kononova, Maria Loleyt, Bas van Stein

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Optimally Weighted Ensembles for Efficient Multi-objective Optimization.

Gideon Hanse, Roy de Winter, Bas van Stein, Thomas Bäck

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Emergence of structural bias in differential evolution.

Bas van Stein, Fabio Caraffini, Anna V. Kononova

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

SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm.

Roy de Winter, Bas van Stein, Thomas Bäck

Proceedings of the Evolutionary Multi-Criterion Optimization, 2021

Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders.

Thiago Rios, Bas van Stein, Patricia Wollstadt, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

Proceedings of the IEEE Congress on Evolutionary Computation, 2021

Requirements towards optimizing analytics in industrial processes.

Alexander Zeiser, Bas van Stein, Thomas Bäck

Proceedings of the 12th International Conference on Ambient Systems, 2021

Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization.

Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

Proceedings of the International Conference on 3D Vision, 2021

2020

A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling.

Yali Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck

CoRR, 2020

Cluster-based Kriging approximation algorithms for complexity reduction.

Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck

Appl. Intell., 2020

A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling.

Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Neural Network Design: Learning from Neural Architecture Search.

Bas van Stein, Hao Wang, Thomas Bäck

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds.

Thiago Rios, Jiawen Kong, Bas van Stein, Thomas Bäck, Patricia Wollstadt, Bernhard Sendhoff, Stefan Menzel

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Feature Visualization for 3D Point Cloud Autoencoders.

Thiago Rios, Bas van Stein, Stefan Menzel, Thomas Bäck, Bernhard Sendhoff, Patricia Wollstadt

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search.

Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019

Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders.

Thiago Rios, Patricia Wollstadt, Bas van Stein, Thomas Bäck, Zhao Xu, Bernhard Sendhoff, Stefan Menzel

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization.

Thiago Rios, Bernhard Sendhoff, Stefan Menzel, Thomas Bäck, Bas van Stein

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem.

Xin Guo, Bas van Stein, Thomas Bäck

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization.

Bas van Stein, Hao Wang, Thomas Bäck

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Automatic Configuration of Deep Neural Networks with EGO.

Bas van Stein, Hao Wang, Thomas Bäck

CoRR, 2018

Designing Ships Using Constrained Multi-objective Efficient Global Optimization.

Roy de Winter, Bas van Stein, Matthys Dijkman, Thomas Bäck

Proceedings of the Machine Learning, Optimization, and Data Science, 2018

A Novel Uncertainty Quantification Method for Efficient Global Optimization.

Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications, 2018

2017

A new acquisition function for Bayesian optimization based on the moment-generating function.

Hao Wang, Bas van Stein, Michael Emmerich, Thomas Bäck

Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

A multi-method simulation of a high-frequency bus line.

Thierry van der Spek, Bas van Stein, Marcel van der Holst, Thomas Bäck

Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Algorithm configuration data mining for CMA evolution strategies.

Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Time complexity reduction in efficient global optimization using cluster kriging.

Hao Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

2016

A framework for evaluating meta-models for simulation-based optimisation.

Pepijn Van Heiningen, Bas van Stein, Thomas Bäck

Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Analysis and Visualization of Missing Value Patterns.

Bas van Stein, Wojtek Kowalczyk, Thomas Bäck

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

An Incremental Algorithm for Repairing Training Sets with Missing Values.

Bas van Stein, Wojtek Kowalczyk

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

Fuzzy clustering for Optimally Weighted Cluster Kriging.

Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck

Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, 2016

Local subspace-based outlier detection using global neighbourhoods.

Bas van Stein, Matthijs van Leeuwen, Thomas Bäck

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Optimally Weighted Cluster Kriging for Big Data Regression.

Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015