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ORCIDNiki van Stein
Bas van Stein
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- affiliation: Leiden University, The Netherlands
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2020 – today
- 2024
[j12]Roy de Winter
, Bas Milatz, Julian Blank, Niki van Stein, Thomas Bäck, Kalyanmoy Deb:
Parallel multi-objective optimization for expensive and inexpensive objectives and constraints. Swarm Evol. Comput. 86: 101508 (2024)- [j11]Fu Xing Long, Bas van Stein, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck:
Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization. ACM Trans. Evol. Learn. Optim. 4(2): 9 (2024) - [c48]Kirill Antonov, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein, Anna V. Kononova:
A Functional Analysis Approach to Symbolic Regression. GECCO 2024 - [c47]Roy de Winter, Bas Milatz, Julian Blank, Niki van Stein, Thomas Bäck, Kalyanmoy Deb:
Hot off the Press: Parallel Multi-Objective Optimization for Expensive and Inexpensive Objectives and Constraints. GECCO Companion 2024: 31-32 - [c46]Roy de Winter, Thomas Bäck, Niki van Stein:
Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems. GECCO Companion 2024: 1715-1723 - [c45]Martijn Halsema, Diederick Vermetten, Thomas Bäck, Niki van Stein:
A Critical Analysis of Raven Roost Optimization. GECCO Companion 2024: 1993-2001 - [c44]Ananta Shahane, Niki van Stein, Yingjie Fan:
A Corridor Model Evolutionary Algorithm for Fast Converging Green Vehicle Routing Problem. GECCO Companion 2024: 2131-2134 - [c43]Niki van Stein, Sarah L. Thomson, Anna V. Kononova:
A Deep Dive Into Effects of Structural Bias on CMA-ES Performance Along Affine Trajectories. PPSN (2) 2024: 36-50 - [c42]Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck, Niki van Stein:
Landscape-Aware Automated Algorithm Configuration Using Multi-output Mixed Regression and Classification. PPSN (2) 2024: 87-104 - [c41]Qi Huang, Emanuele Mezzi, Osman Mutlu, Miltiadis Kofinas, Vidya Prasad, Shadnan Azwad Khan, Elena Ranguelova, Niki van Stein:
Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI. xAI (1) 2024: 308-331 - [i28]Niki van Stein, Diederick Vermetten, Anna V. Kononova, Thomas Bäck:
Explainable Benchmarking for Iterative Optimization Heuristics. CoRR abs/2401.17842 (2024) - [i27]Qi Huang, Wei Chen, Thomas Bäck, Niki van Stein:
Shapelet-based Model-agnostic Counterfactual Local Explanations for Time Series Classification. CoRR abs/2402.01343 (2024) - [i26]Kirill Antonov, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein, Anna V. Kononova:
A Functional Analysis Approach to Symbolic Regression. CoRR abs/2402.06299 (2024) - [i25]Niki van Stein, Sarah L. Thomson, Anna V. Kononova:
A Deep Dive into Effects of Structural Bias on CMA-ES Performance along Affine Trajectories. CoRR abs/2404.17323 (2024) - [i24]Christian Internò, Elena Raponi, Niki van Stein, Thomas Bäck, Markus Olhofer, Yaochu Jin, Barbara Hammer:
Automated Federated Learning via Informed Pruning. CoRR abs/2405.10271 (2024) - [i23]Niki van Stein, Thomas Bäck:
LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics. CoRR abs/2405.20132 (2024) - [i22]Gjorgjina Cenikj, Ana Nikolikj, Gasper Petelin, Niki van Stein, Carola Doerr, Tome Eftimov:
A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization. CoRR abs/2406.06629 (2024) - [i21]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:
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. CoRR abs/2406.07811 (2024) - [i20]Aske Plaat, Annie Wong, Suzan Verberne, Joost Broekens, Niki van Stein, Thomas Bäck:
Reasoning with Large Language Models, a Survey. CoRR abs/2407.11511 (2024) - [i19]Qi Huang, Emanuele Mezzi, Osman Mutlu, Miltiadis Kofinas, Vidya Prasad, Shadnan Azwad Khan, Elena Ranguelova, Niki van Stein:
Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI. CoRR abs/2407.12950 (2024) - [i18]Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck, Niki van Stein:
Landscape-Aware Automated Algorithm Configuration using Multi-output Mixed Regression and Classification. CoRR abs/2409.01446 (2024) - [i17]Qi Huang, Sofoklis Kitharidis, Thomas Bäck, Niki van Stein:
TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification. CoRR abs/2409.09461 (2024) - 2023
- [j10]Alexander Zeiser, Bekir Özcan, Christoph Kracke, Bas van Stein, Thomas Bäck:
A data-centric approach to anomaly detection in layer-based additive manufacturing. Autom. 71(1): 81-89 (2023) - [j9]Alexander Zeiser, Bekir Özcan, Bas van Stein, Thomas Bäck:
Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection. Comput. Ind. 146: 103852 (2023) - [j8]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): 81-122 (2023) - [c40]Fu Xing Long, Diederick Vermetten, Bas van Stein, Anna V. Kononova:
BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances. EvoApplications@EvoStar 2023: 380-395 - [c39]Kirill A. Antonov, Anna V. Kononova, Thomas Bäck, Niki van Stein:
Curing ill-Conditionality via Representation-Agnostic Distance-Driven Perturbations. FOGA 2023: 15-26 - [c38]Bas van Stein, Diederick Vermetten, Fabio Caraffini, Anna V. Kononova:
Deep BIAS: Detecting Structural Bias using Explainable AI. GECCO Companion 2023: 455-458 - [c37]Bas van Stein, Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck:
DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis. GECCO Companion 2023: 515-518 - [c36]Christiaan Lamers, René Vidal, Nabil Belbachir, Niki van Stein, Thomas Bäck, Paris Giampouras:
Clustering-based Domain-Incremental Learning. ICCV (Workshops) 2023: 3376-3384 - [c35]Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein:
Challenges of ELA-Guided Function Evolution Using Genetic Programming. IJCCI 2023: 119-130 - [c34]Sarah L. Thomson, Niki van Stein, Daan van den Berg, Cees van Leeuwen:
The Opaque Nature of Intelligence and the Pursuit of Explainable AI. IJCCI 2023: 555-564 - [e2]Niki van Stein, Francesco Marcelloni, H. K. Lam, Marie Cottrell, Joaquim Filipe:
Proceedings of the 15th International Joint Conference on Computational Intelligence, IJCCI 2023, Rome, Italy, November 13-15, 2023. SCITEPRESS 2023, ISBN 978-989-758-674-3 [contents] - [d1]Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein:
Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files. Zenodo, 2023
- [i16]Bas van Stein, Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck:
DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis. CoRR abs/2304.01219 (2023) - [i15]Bas van Stein, Diederick Vermetten, Fabio Caraffini, Anna V. Kononova:
Deep-BIAS: Detecting Structural Bias using Explainable AI. CoRR abs/2304.01869 (2023) - [i14]Fu Xing Long, Diederick Vermetten, Anna V. Kononova, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein:
Challenges of ELA-guided Function Evolution using Genetic Programming. CoRR abs/2305.15245 (2023) - [i13]Kirill Antonov, Anna V. Kononova, Thomas Bäck, Niki van Stein:
Representation-agnostic distance-driven perturbation for optimizing ill-conditioned problems. CoRR abs/2306.02985 (2023) - [i12]Christiaan Lamers, René Vidal, Ahmed Nabil Belbachir, Niki van Stein, Thomas Bäck, Paris Giampouras:
Clustering-based Domain-Incremental Learning. CoRR abs/2309.12078 (2023) - 2022
- [j7]Bas van Stein, Elena Raponi, Zahra Sadeghi, Niek Bouman, Roeland C. H. J. van Ham, Thomas Bäck:
A Comparison of Global Sensitivity Analysis Methods for Explainable AI With an Application in Genomic Prediction. IEEE Access 10: 103364-103381 (2022) - [j6]Marios Kefalas, Juan de Santiago Rojo Jr., Asteris Apostolidis, Dirk van den Herik, Bas van Stein, Thomas Bäck:
Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines. J. Aerosp. Inf. Syst. 19(6): 447-454 (2022) - [j5]Bas van Stein, Elena Raponi:
GSAreport: Easy to Use Global Sensitivity Reporting. J. Open Source Softw. 7(78): 4721 (2022) - [j4]Roy de Winter, Philip Bronkhorst, Bas van Stein, Thomas Bäck:
Constrained Multi-Objective Optimization with a Limited Budget of Function Evaluations. Memetic Comput. 14(2): 151-164 (2022) - [j3]Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel:
Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation. IEEE Trans. Evol. Comput. 26(2): 206-217 (2022) - [j2]Diederick Vermetten, Bas van Stein, Fabio Caraffini, Leandro L. Minku, Anna V. Kononova:
BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain. IEEE Trans. Evol. Comput. 26(6): 1380-1393 (2022) - [c33]Roy de Winter, Bas van Stein, Thomas Bäck:
Multi-point acquisition function for constraint parallel efficient multi-objective optimization. GECCO 2022: 511-519 - [c32]Fu Xing Long, Bas van Stein, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck:
Learning the characteristics of engineering optimization problems with applications in automotive crash. GECCO 2022: 1227-1236 - [c31]Diederick Vermetten, Fabio Caraffini, Bas van Stein, Anna V. Kononova:
Using structural bias to analyse the behaviour of modular CMA-ES. GECCO Companion 2022: 1674-1682 - [c30]Qi Huang, Roy de Winter, Bas van Stein, Thomas Bäck, Anna V. Kononova:
Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems. SSCI 2022: 1650-1658 - [e1]Thomas Bäck, Bas van Stein, Christian Wagner, Jonathan M. Garibaldi, H. K. Lam, Marie Cottrell, Faiyaz Doctor, Joaquim Filipe, Kevin Warwick, Janusz Kacprzyk:
Proceedings of the 14th International Joint Conference on Computational Intelligence, IJCCI 2022, Valletta, Malta, October 24-26, 2022. SCITEPRESS 2022, ISBN 978-989-758-611-8 [contents] - [i11]Koen Ponse, Anna V. Kononova, Maria Loleyt, Bas van Stein:
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images. CoRR abs/2201.06594 (2022) - [i10]Marios Kefalas, Juan de Santiago Rojo Jr., Asteris Apostolidis, Dirk van den Herik, Bas van Stein, Thomas Bäck:
Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines. CoRR abs/2203.13108 (2022) - [i9]Alexander Zeiser, Bas van Stein, Thomas Bäck:
Deep Learning based pipeline for anomaly detection and quality enhancement in industrial binder jetting processes. CoRR abs/2209.10178 (2022) - [i8]Fu Xing Long, Diederick Vermetten, Bas van Stein, Anna V. Kononova:
BBOB Instance Analysis: Landscape Properties and Algorithm Performance across Problem Instances. CoRR abs/2211.16318 (2022) - [i7]Qi Huang, Roy de Winter, Bas van Stein, Thomas Bäck, Anna V. Kononova:
Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems. CoRR abs/2212.06438 (2022) - 2021
- [c29]Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel:
Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization. 3DV 2021: 1024-1033 - [c28]Alexander Zeiser, Bas van Stein, Thomas Bäck:
Requirements towards optimizing analytics in industrial processes. ANT/EDI40 2021: 597-605 - [c27]Thiago Rios, Bas van Stein, Patricia Wollstadt, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel:
Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders. CEC 2021: 514-521 - [c26]Roy de Winter, Bas van Stein, Thomas Bäck:
SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm. EMO 2021: 270-282 - [c25]Bas van Stein, Fabio Caraffini, Anna V. Kononova:
Emergence of structural bias in differential evolution. GECCO Companion 2021: 1234-1242 - [c24]Gideon Hanse, Roy de Winter, Bas van Stein, Thomas Bäck:
Optimally Weighted Ensembles for Efficient Multi-objective Optimization. LOD 2021: 144-156 - [c23]Koen Ponse, Anna V. Kononova, Maria Loleyt, Bas van Stein:
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images. SSCI 2021: 1-8 - [c22]Sneha Saha, Thiago Rios, Leandro L. Minku, Bas van Stein, Patricia Wollstadt, Xin Yao, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel:
Exploiting Generative Models for Performance Predictions of 3D Car Designs. SSCI 2021: 1-9 - [i6]Bas van Stein, Fabio Caraffini, Anna V. Kononova:
Emergence of Structural Bias in Differential Evolution. CoRR abs/2105.04693 (2021) - 2020
- [j1]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck:
Cluster-based Kriging approximation algorithms for complexity reduction. Appl. Intell. 50(3): 778-791 (2020) - [c21]Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich:
Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search. GECCO Companion 2020: 181-182 - [c20]Thiago Rios, Bas van Stein, Stefan Menzel, Thomas Bäck, Bernhard Sendhoff, Patricia Wollstadt:
Feature Visualization for 3D Point Cloud Autoencoders. IJCNN 2020: 1-9 - [c19]Thiago Rios, Jiawen Kong, Bas van Stein, Thomas Bäck, Patricia Wollstadt, Bernhard Sendhoff, Stefan Menzel:
Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds. SSCI 2020: 942-949 - [c18]Bas van Stein, Hao Wang, Thomas Bäck:
Neural Network Design: Learning from Neural Architecture Search. SSCI 2020: 1341-1349 - [c17]Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich:
A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling. SSCI 2020: 2746-2753 - [i5]Yali Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck:
A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling. CoRR abs/2004.06564 (2020) - [i4]Bas van Stein, Hao Wang, Thomas Bäck:
Neural Network Design: Learning from Neural Architecture Search. CoRR abs/2011.00521 (2020)
2010 – 2019
- 2019
- [c16]Bas van Stein, Hao Wang, Thomas Bäck:
Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization. IJCNN 2019: 1-7 - [c15]Thiago Rios, Bernhard Sendhoff, Stefan Menzel, Thomas Bäck, Bas van Stein:
On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization. SSCI 2019: 791-798 - [c14]Thiago Rios, Patricia Wollstadt, Bas van Stein, Thomas Bäck, Zhao Xu, Bernhard Sendhoff, Stefan Menzel:
Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders. SSCI 2019: 1367-1374 - [c13]Xin Guo, Bas van Stein, Thomas Bäck:
A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem. SSCI 2019: 2042-2049 - 2018
- [c12]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck:
A Novel Uncertainty Quantification Method for Efficient Global Optimization. IPMU (3) 2018: 480-491 - [c11]Roy de Winter, Bas van Stein, Matthys Dijkman, Thomas Bäck:
Designing Ships Using Constrained Multi-objective Efficient Global Optimization. LOD 2018: 191-203 - [i3]Bas van Stein, Hao Wang, Thomas Bäck:
Automatic Configuration of Deep Neural Networks with EGO. CoRR abs/1810.05526 (2018) - 2017
- [c10]Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck:
Algorithm configuration data mining for CMA evolution strategies. GECCO 2017: 737-744 - [c9]Hao Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck:
Time complexity reduction in efficient global optimization using cluster kriging. GECCO 2017: 889-896 - [c8]Thierry van der Spek, Bas van Stein, Marcel van der Holst, Thomas Bäck:
A multi-method simulation of a high-frequency bus line. ITSC 2017: 1-6 - [c7]Hao Wang, Bas van Stein, Michael Emmerich, Thomas Bäck:
A new acquisition function for Bayesian optimization based on the moment-generating function. SMC 2017: 507-512 - [i2]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Cluster-based Kriging Approximation Algorithms for Complexity Reduction. CoRR abs/1702.01313 (2017) - 2016
- [c6]Bas van Stein, Matthijs van Leeuwen, Thomas Bäck:
Local subspace-based outlier detection using global neighbourhoods. IEEE BigData 2016: 1136-1142 - [c5]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Fuzzy clustering for Optimally Weighted Cluster Kriging. FUZZ-IEEE 2016: 939-945 - [c4]Bas van Stein, Wojtek Kowalczyk:
An Incremental Algorithm for Repairing Training Sets with Missing Values. IPMU (2) 2016: 175-186 - [c3]Bas van Stein, Wojtek Kowalczyk, Thomas Bäck:
Analysis and Visualization of Missing Value Patterns. IPMU (2) 2016: 187-198 - [c2]Pepijn Van Heiningen, Bas van Stein, Thomas Bäck:
A framework for evaluating meta-models for simulation-based optimisation. SSCI 2016: 1-8 - [i1]Bas van Stein, Matthijs van Leeuwen, Thomas Bäck:
Local Subspace-Based Outlier Detection using Global Neighbourhoods. CoRR abs/1611.00183 (2016) - 2015
- [c1]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich:
Optimally Weighted Cluster Kriging for Big Data Regression. IDA 2015: 310-321
Coauthor Index
Thomas Bäck
aka: Thomas H. W. Bäck
aka: Thomas H. W. Bäck
[j12] [j11] [c48] [c47] [c46] [c45] [c42] [i28] [i27] [i26] [i24] [i23] [i20] [i18] [i17] [j10] [j9] [j8] [c39] [c37] [c36] [c35] [d1] [i16] [i14] [i13] [i12] [j7] [j6] [j4] [j3] [c33] [c32] [c30] [e1] [i10] [i9] [i7] [c29] [c28] [c27] [c26] [c24] [c22] [j1] [c21] [c20] [c19] [c18] [c17] [i5] [i4] [c16] [c15] [c14] [c13] [c12] [c11] [i3] [c10] [c9] [c8] [c7] [i2] [c6] [c5] [c3] [c2] [i1] [c1]
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