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Thomas H. W. Bäck
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- affiliation: Leiden Institute of Advanced Computer Science, Netherlands
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2020 – today
- 2025
[j70]Lucas Correia, Jan-Christoph Goos, Philipp Klein, Thomas Bäck, Anna V. Kononova:
Corrigendum to "Online model-based anomaly detection in multivariate time series: Taxonomy, survey, research challenges and future directions" [Eng. Appl. Artif. Intell. 138 (2024) 109323]. Eng. Appl. Artif. Intell. 145: 110170 (2025)- [j69]Niki van Stein
, Thomas Bäck:
LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics. IEEE Trans. Evol. Comput. 29(2): 331-345 (2025) - [j68]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts. ACM Trans. Evol. Learn. Optim. 5(1): 1-19 (2025) - [c288]Ksenia Pereverdieva, André H. Deutz, Tessa Ezendam, Thomas Bäck, Hèrm Hofmeyer, Michael T. M. Emmerich:
Comparative Analysis of Indicators for Multi-objective Diversity Optimization. EMO (2) 2025: 58-71 - [c287]Diederick Vermetten, Jeroen Rook, Oliver L. Preuß, Jacob de Nobel, Carola Doerr, Manuel López-Ibáñez, Heike Trautmann, Thomas Bäck:
MO-IOHinspector: Anytime Benchmarking of Multi-objective Algorithms Using IOHprofiler. EMO (1) 2025: 242-256 - [c286]Haoran Yin, Anna V. Kononova, Thomas Bäck, Niki van Stein:
Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms. EvoApplications (2) 2025: 403-417 - [i121]Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang:
Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks. CoRR abs/2501.14012 (2025) - [i120]Georgios Andreadis, Eduard Ruiz Munné, Thomas H. W. Bäck, Peter A. N. Bosman, Tanja Alderliesten:
Multi-Objective Deep-Learning-based Biomechanical Deformable Image Registration with MOREA. CoRR abs/2501.16525 (2025) - [i119]Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang:
Transfer Learning of Surrogate Models: Integrating Domain Warping and Affine Transformations. CoRR abs/2501.18344 (2025) - [i118]Jacob de Nobel, Diederick Vermetten, Hao Wang, Anna V. Kononova, Günter Rudolph, Thomas Bäck:
Abnormal Mutations: Evolution Strategies Don't Require Gaussianity. CoRR abs/2502.03148 (2025) - [i117]Shuaiqun Pan, Yash J. Patel, Aneta Neumann, Frank Neumann, Thomas Bäck, Hao Wang:
Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms. CoRR abs/2502.12012 (2025) - [i116]Zhong Li, Qi Huang, Lincen Yang, Jiayang Shi, Zhao Yang, Niki van Stein, Thomas Bäck, Matthijs van Leeuwen:
Diffusion Models for Tabular Data: Challenges, Current Progress, and Future Directions. CoRR abs/2502.17119 (2025) - [i115]Jiajie Fan, Amal Trigui, Andrea Bonfanti, Felix Dietrich, Thomas Bäck, Hao Wang:
A Mesh Is Worth 512 Numbers: Spectral-domain Diffusion Modeling for High-dimension Shape Generation. CoRR abs/2503.06485 (2025) - [i114]Niki van Stein, Anna V. Kononova, Lars Kotthoff, Thomas Bäck:
Code Evolution Graphs: Understanding Large Language Model Driven Design of Algorithms. CoRR abs/2503.16668 (2025) - [i113]Haoran Yin, Anna V. Kononova, Thomas Bäck, Niki van Stein:
Optimizing Photonic Structures with Large Language Model Driven Algorithm Discovery. CoRR abs/2503.19742 (2025) - [i112]Samuel Bonello, Rachel G. de Jong, Thomas H. W. Bäck, Frank W. Takes:
Utility-aware Social Network Anonymization using Genetic Algorithms. CoRR abs/2504.05183 (2025) - [i111]Niki van Stein, Anna V. Kononova, Haoran Yin, Thomas Bäck:
BLADE: Benchmark suite for LLM-driven Automated Design and Evolution of iterative optimisation heuristics. CoRR abs/2504.20183 (2025) - 2024
- [j67]Mitra Baratchi, Can Wang, Steffen Limmer, Jan N. van Rijn, Holger H. Hoos, Thomas Bäck, Markus Olhofer:
Automated machine learning: past, present and future. Artif. Intell. Rev. 57(5): 122 (2024) - [j66]Lucas Correia, Jan-Christoph Goos, Philipp Klein, Thomas Bäck, Anna V. Kononova:
Online model-based anomaly detection in multivariate time series: Taxonomy, survey, research challenges and future directions. Eng. Appl. Artif. Intell. 138: 109323 (2024) - [j65]Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. Evol. Comput. 32(3): 205-210 (2024) - [j64]Charles Moussa, Yash J. Patel, Vedran Dunjko, Thomas Bäck, Jan N. van Rijn:
Hyperparameter importance and optimization of quantum neural networks across small datasets. Mach. Learn. 113(4): 1941-1966 (2024) - [j63]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) - [j62]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) - [c285]Wei Liu, Thomas Bäck, Yingjie Fan:
Cluster-Centric Local Search Strategies for Enhanced Multi-Objective Logistics Optimization. CEC 2024: 1-8 - [c284]Jiajie Fan, Amal Trigui, Thomas Bäck, Hao Wang:
Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder. ECCV (78) 2024: 88-105 - [c283]Qi Huang, Sofoklis Kitharidis, Thomas Bäck, Niki van Stein:
TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification. EXPLAINS 2024: 62-74 - [c282]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 - [c281]Kirill Antonov, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein, Anna V. Kononova:
A Functional Analysis Approach to Symbolic Regression. GECCO 2024 - [c280]Carola Doerr, Diederick Vermetten, Jacob de Nobel, Thomas Bäck:
Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. GECCO Companion 2024: 791-799 - [c279]Martijn Halsema, Diederick Vermetten, Thomas Bäck, Niki van Stein:
A Critical Analysis of Raven Roost Optimization. GECCO Companion 2024: 1993-2001 - [c278]Roman Kalkreuth, Thomas Bäck:
CGP++ : A Modern C++ Implementation of Cartesian Genetic Programming. GECCO 2024 - [c277]Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang:
Transfer Learning of Surrogate Models via Domain Affine Transformation. GECCO 2024 - [c276]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. GECCO 2024 - [c275]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 - [c274]Roy de Winter, Thomas Bäck, Niki van Stein:
Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems. GECCO Companion 2024: 1715-1723 - [c273]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 - [c272]Haoran Yin, Diederick Vermetten, Furong Ye, Thomas H. W. Bäck, Anna V. Kononova:
Impact of Spatial Transformations on Exploratory and Deep-Learning Based Landscape Features of CEC2022 Benchmark Suite. IJCCI 2024: 60-71 - [c271]Jacob de Nobel, Diederick Vermetten, Thomas H. W. Bäck, Anna V. Kononova:
Sampling in CMA-ES: Low Numbers of Low Discrepancy Points. IJCCI 2024: 120-126 - [c270]Maarten C. Vonk, Diederick Vermetten, Jacob de Nobel, Sebastiaan Brand, Ninoslav Malekovic, Thomas Bäck, Alfons Laarman, Anna V. Kononova:
Optimizing Causal Interventions in Hybrid Bayesian Networks - A Discretization, Knowledge Compilation, and Heuristic Optimization Approach. IPMU (1) 2024: 245-256 - [c269]Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr:
Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler. PPSN (2) 2024: 20-35 - [c268]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 - [c267]Jacob de Nobel, Diederick Vermetten, Anna V. Kononova, Ofer M. Shir, Thomas Bäck:
Avoiding Redundant Restarts in Multimodal Global Optimization. PPSN (2) 2024: 268-283 - [e14]Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann, Tea Tusar, Penousal Machado, Thomas Bäck:
Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15148, Springer 2024, ISBN 978-3-031-70054-5 [contents] - [e13]Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann, Tea Tusar, Penousal Machado, Thomas Bäck:
Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part II. Lecture Notes in Computer Science 15149, Springer 2024, ISBN 978-3-031-70067-5 [contents] - [e12]Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann, Tea Tusar, Penousal Machado, Thomas Bäck:
Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III. Lecture Notes in Computer Science 15150, Springer 2024, ISBN 978-3-031-70070-5 [contents] - [e11]Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann, Tea Tusar, Penousal Machado, Thomas Bäck:
Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 15151, Springer 2024, ISBN 978-3-031-70084-2 [contents] - [d23]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics - Reproducibility Files. Zenodo, 2024
- [d22]Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr:
Benchmarking Dynamic Binary Value Problems with IOHprofiler - Reproducibility files. Zenodo, 2024 - [d21]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB - Reproducibility and Additional Data. Version 2. Zenodo, 2024 [all versions] - [d20]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB - Reproducibility and Additional Data. Zenodo, 2024 - [i110]Niki van Stein, Diederick Vermetten, Anna V. Kononova, Thomas Bäck:
Explainable Benchmarking for Iterative Optimization Heuristics. CoRR abs/2401.17842 (2024) - [i109]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) - [i108]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) - [i107]Annie Wong, Jacob de Nobel, Thomas Bäck, Aske Plaat, Anna V. Kononova:
Solving Deep Reinforcement Learning Benchmarks with Linear Policy Networks. CoRR abs/2402.06912 (2024) - [i106]Haoran Yin, Diederick Vermetten, Furong Ye, Thomas H. W. Bäck, Anna V. Kononova:
Impact of spatial transformations on landscape features of CEC2022 basic benchmark problems. CoRR abs/2402.07654 (2024) - [i105]Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-scale Benchmarking of Metaphor-based Optimization Heuristics. CoRR abs/2402.09800 (2024) - [i104]Jiajie Fan, Amal Trigui, Thomas Bäck, Hao Wang:
Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder. CoRR abs/2403.05352 (2024) - [i103]Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr:
Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler. CoRR abs/2404.15837 (2024) - [i102]Jacob de Nobel, Diederick Vermetten, Anna V. Kononova, Ofer M. Shir, Thomas Bäck:
Avoiding Redundant Restarts in Multimodal Global Optimization. CoRR abs/2405.01226 (2024) - [i101]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) - [i100]Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann:
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. CoRR abs/2405.18772 (2024) - [i99]Niki van Stein, Thomas Bäck:
LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics. CoRR abs/2405.20132 (2024) - [i98]Roman Kalkreuth, Thomas Bäck:
CGP++ : A Modern C++ Implementation of Cartesian Genetic Programming. CoRR abs/2406.09038 (2024) - [i97]Lucas Correia, Jan-Christoph Goos, Philipp Klein, Thomas Bäck, Anna V. Kononova:
TeVAE: A Variational Autoencoder Approach for Discrete Online Anomaly Detection in Variable-state Multivariate Time-series Data. CoRR abs/2407.06849 (2024) - [i96]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) - [i95]Lucas Correia, Jan-Christoph Goos, Philipp Klein, Thomas Bäck, Anna V. Kononova:
Online Model-based Anomaly Detection in Multivariate Time Series: Taxonomy, Survey, Research Challenges and Future Directions. CoRR abs/2408.03747 (2024) - [i94]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) - [i93]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) - [i92]Ismail Labiad, Thomas Bäck, Pierre Fernandez, Laurent Najman, Tom Sander, Furong Ye, Mariia Zameshina, Olivier Teytaud:
Log-normal Mutations and their Use in Detecting Surreptitious Fake Images. CoRR abs/2409.15119 (2024) - [i91]Jacob de Nobel, Diederick Vermetten, Thomas H. W. Bäck, Anna V. Kononova:
Sampling in CMA-ES: Low Numbers of Low Discrepancy Points. CoRR abs/2409.15941 (2024) - [i90]Kirill A. Antonov, Marijn Siemons, Niki van Stein, Thomas H. W. Bäck, Ralf Kohlhaas, Anna V. Kononova:
Selection of Filters for Photonic Crystal Spectrometer Using Domain-Aware Evolutionary Algorithms. CoRR abs/2410.13657 (2024) - [i89]Niki van Stein, Diederick Vermetten, Thomas Bäck:
In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics. CoRR abs/2410.16309 (2024) - [i88]Ksenia Pereverdieva, André H. Deutz, Tessa Ezendam, Thomas Bäck, Hèrm Hofmeyer, Michael T. M. Emmerich:
Comparative Analysis of Indicators for Multiobjective Diversity Optimization. CoRR abs/2410.18900 (2024) - [i87]Jiajie Fan, Babak Gholami, Thomas Bäck, Hao Wang:
NeuroNURBS: Learning Efficient Surface Representations for 3D Solids. CoRR abs/2411.10848 (2024) - [i86]Lucas Correia, Jan-Christoph Goos, Thomas Bäck, Anna V. Kononova:
A Dataset for Evaluating Online Anomaly Detection Approaches for Discrete Multivariate Time Series. CoRR abs/2411.13951 (2024) - [i85]Haoran Yin, Anna V. Kononova, Thomas Bäck, Niki van Stein:
Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms. CoRR abs/2412.03250 (2024) - [i84]Diederick Vermetten, Jeroen Rook, Oliver Ludger Preuß, Jacob de Nobel, Carola Doerr, Manuel López-Ibáñez, Heike Trautmann, Thomas Bäck:
MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler. CoRR abs/2412.07444 (2024) - 2023
- [j61]Annie Wong, Thomas Bäck, Anna V. Kononova, Aske Plaat:
Deep multiagent reinforcement learning: challenges and directions. Artif. Intell. Rev. 56(6): 5023-5056 (2023) - [j60]Maarten C. Vonk, Ninoslav Malekovic, Thomas Bäck, Anna V. Kononova:
Disentangling causality: assumptions in causal discovery and inference. Artif. Intell. Rev. 56(9): 10613-10649 (2023) - [j59]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) - [j58]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) - [j57]Haotian Zhang, Jianyong Sun, Thomas Bäck, Qingfu Zhang, Zongben Xu:
Controlling Sequential Hybrid Evolutionary Algorithm by Q-Learning [Research Frontier] [Research Frontier]. IEEE Comput. Intell. Mag. 18(1): 84-103 (2023) - [j56]Xishu Li, Maurits de Groot, Thomas Bäck:
Using forecasting to evaluate the impact of COVID-19 on passenger air transport demand. Decis. Sci. 54(4): 394-409 (2023) - [j55]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) - [j54]Zhengtian Ai, Ingo Heinle, Christian Schelske, Hao Wang, Peter Krause, Thomas Bäck:
Classification-based process parameter recommendation in sheet metal forming. J. Ind. Inf. Integr. 34: 100458 (2023) - [j53]Dani Irawan, Boris Naujoks, Thomas Bäck, Michael Emmerich:
Dominance-based variable analysis for large-scale multi-objective problems. Nat. Comput. 22(2): 243-257 (2023) - [c266]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts. AutoML 2023: 7/1-14 - [c265]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: 1-9 - [c264]David Von Dollen, Reuben Brasher, Florian Neukart, Thomas Bäck:
Hyperparameter Optimization and Neuroevolution with Binary Quadratic Meta-heuristics and Evolution Strategies. CiSt 2023: 536-540 - [c263]Ksenia Pereverdieva, Michael Emmerich, André H. Deutz, Tessa Ezendam, Thomas Bäck, Hèrm Hofmeyer:
The Prism-Net Search Space Representation for Multi-objective Building Spatial Design. EMO 2023: 476-489 - [c262]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm Versus Column Generation Method. EMO 2023: 518-531 - [c261]André Thomaser, Marc-Eric Vogt, Anna V. Kononova, Thomas Bäck:
Transfer of Multi-objectively Tuned CMA-ES Parameters to a Vehicle Dynamics Problem. EMO 2023: 546-560 - [c260]Sebastiaan Brand, Thomas Bäck, Alfons Laarman:
A Decision Diagram Operation for Reachability. FM 2023: 514-532 - [c259]Kirill A. Antonov, Anna V. Kononova, Thomas Bäck, Niki van Stein:
Curing ill-Conditionality via Representation-Agnostic Distance-Driven Perturbations. FOGA 2023: 15-26 - [c258]Roman Kalkreuth, Zdenek Vasícek, Jakub Husa, Diederick Vermetten, Furong Ye, Thomas Bäck:
General Boolean Function Benchmark Suite. FOGA 2023: 84-95 - [c257]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 - [c256]Roman Kalkreuth, Zdenek Vasícek, Jakub Husa, Diederick Vermetten, Furong Ye, Thomas Bäck:
Towards a General Boolean Function Benchmark Suite. GECCO Companion 2023: 591-594 - [c255]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: 856-863 - [c254]Diederick Vermetten, Fabio Caraffini, Anna V. Kononova, Thomas Bäck:
Modular Differential Evolution. GECCO 2023: 864-872 - [c253]Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye:
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion 2023: 938-945 - [c252]Christiaan Lamers, René Vidal, Nabil Belbachir, Niki van Stein, Thomas Bäck, Paris Giampouras:
Clustering-based Domain-Incremental Learning. ICCV (Workshops) 2023: 3376-3384 - [c251]André Thomaser, Marc-Eric Vogt, Thomas Bäck, Anna V. Kononova:
Real-World Optimization Benchmark from Vehicle Dynamics: Specification of Problems in 2D and Methodology for Transferring (Meta-)Optimized Algorithm Parameters. IJCCI 2023: 31-40 - [c250]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 - [c249]André Thomaser, Marc-Eric Vogt, Thomas Bäck, Anna V. Kononova:
Optimizing CMA-ES with CMA-ES. IJCCI 2023: 214-221 - [c248]Lucas Correia, Jan-Christoph Goos, Philipp Klein, Thomas Bäck, Anna V. Kononova:
MA-VAE: Multi-Head Attention-Based Variational Autoencoder Approach for Anomaly Detection in Multivariate Time-Series Applied to Automotive Endurance Powertrain Testing. IJCCI 2023: 407-418 - [c247]Waheeda Saib, Xavier Bonet-Monroig, Vedran Dunjko, Ivano Tavernelli, Thomas Bäck, Hao Wang:
Benchmarking Adaptive Quantum Circuit Optimization Algorithms for Quantum Chemistry. QCE 2023: 83-88 - [c246]Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko:
Application of quantum-inspired generative models to small molecular datasets. QCE 2023: 342-348 - [d19]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 - [d18]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB - Reproducibility and Additional Data. Version 1. Zenodo, 2023 [all versions] - [i83]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 abs/2302.01464 (2023) - [i82]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 abs/2303.04611 (2023) - [i81]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) - [i80]Diederick Vermetten, Fabio Caraffini, Anna V. Kononova, Thomas Bäck:
Modular Differential Evolution. CoRR abs/2304.09524 (2023) - [i79]Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko:
Application of quantum-inspired generative models to small molecular datasets. CoRR abs/2304.10867 (2023) - [i78]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 abs/2304.13117 (2023) - [i77]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) - [i76]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) - [i75]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts. CoRR abs/2306.10627 (2023) - [i74]Jiajie Fan, Laure Vuaille, Hao Wang, Thomas Bäck:
Adversarial Latent Autoencoder with Self-Attention for Structural Image Synthesis. CoRR abs/2307.10166 (2023) - [i73]Lucas Correia, Jan-Christoph Goos, Philipp Klein, Thomas Bäck, Anna V. Kononova:
MA-VAE: Multi-head Attention-based Variational Autoencoder Approach for Anomaly Detection in Multivariate Time-series Applied to Automotive Endurance Powertrain Testing. CoRR abs/2309.02253 (2023) - [i72]Christiaan Lamers, René Vidal, Ahmed Nabil Belbachir, Niki van Stein, Thomas Bäck, Paris Giampouras:
Clustering-based Domain-Incremental Learning. CoRR abs/2309.12078 (2023) - [i71]Jiajie Fan, Laure Vuaille, Thomas Bäck, Hao Wang:
On the Noise Scheduling for Generating Plausible Designs with Diffusion Models. CoRR abs/2311.11207 (2023) - [i70]Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr:
MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts. CoRR abs/2312.11083 (2023) - 2022
- [j52]Duc Anh Nguyen, Anna V. Kononova, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
An Efficient Contesting Procedure for AutoML Optimization. IEEE Access 10: 75754-75771 (2022) - [j51]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) - [j50]Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen:
Robust subgroup discovery. Data Min. Knowl. Discov. 36(5): 1885-1970 (2022) - [j49]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) - [j48]Danny Weyns, Thomas Bäck, René Vidal, Xin Yao, Ahmed Nabil Belbachir:
The vision of self-evolving computing systems. J. Integr. Des. Process. Sci. 26(3-4): 351-367 (2022) - [j47]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) - [j46]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) - [j45]Thomas Bäck, Carola Doerr, Bernhard Sendhoff, Thomas Stützle:
Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software. IEEE Trans. Evol. Comput. 26(6): 1202-1205 (2022) - [j44]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. IEEE Trans. Evol. Comput. 26(6): 1526-1538 (2022) - [j43]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics. ACM Trans. Evol. Learn. Optim. 2(1): 3:1-3:29 (2022) - [c245]Charles Moussa, Jan N. van Rijn, Thomas Bäck, Vedran Dunjko:
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets. DS 2022: 32-46 - [c244]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. GECCO Companion 2022: 49-50 - [c243]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. GECCO Companion 2022: 51-52 - [c242]David Von Dollen, Sheir Yarkoni, Daniel Weimer, Florian Neukart, Thomas Bäck:
Quantum-enhanced selection operators for evolutionary algorithms. GECCO Companion 2022: 463-466 - [c241]Roy de Winter, Bas van Stein, Thomas Bäck:
Multi-point acquisition function for constraint parallel efficient multi-objective optimization. GECCO 2022: 511-519 - [c240]Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck:
Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms. GECCO 2022: 867-875 - [c239]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 - [c238]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: 1334-1341 - [c237]Ofer M. Shir, Thomas Bäck:
Sequential experimentation by evolutionary algorithms. GECCO Companion 2022: 1450-1468 - [c236]André Thomaser, Anna V. Kononova, Marc-Eric Vogt, Thomas Bäck:
One-shot optimization for vehicle dynamics control systems: towards benchmarking and exploratory landscape analysis. GECCO Companion 2022: 2036-2045 - [c235]Fan Yang, Marios Kefalas, Milan Koch, Anna V. Kononova, Yanan Qiao, Thomas Bäck:
Auto-REP: An Automated Regression Pipeline Approach for High-efficiency Earthquake Prediction Using LANL Data. ICCAE 2022: 127-134 - [c234]Veysel Kocaman, Ofer M. Shir, Thomas Bäck, Ahmed Nabil Belbachir:
Saliency Can Be All You Need in Contrastive Self-supervised Learning. ISVC (2) 2022: 119-140 - [c233]Furong Ye, Diederick Vermetten, Carola Doerr, Thomas Bäck:
Non-elitist Selection Can Improve the Performance of Irace. PPSN (1) 2022: 32-45 - [c232]Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
A Systematic Approach to Analyze the Computational Cost of Robustness in Model-Assisted Robust Optimization. PPSN (1) 2022: 63-75 - [c231]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 - [p2]Luca Mariot, Domagoj Jakobovic, Thomas Bäck, Julio C. Hernandez-Castro:
Artificial Intelligence for the Design of Symmetric Cryptographic Primitives. Security and Artificial Intelligence 2022: 3-24 - [e10]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] - [e9]Lejla Batina, Thomas Bäck, Ileana Buhan, Stjepan Picek:
Security and Artificial Intelligence - A Crossdisciplinary Approach. Lecture Notes in Computer Science 13049, Springer 2022, ISBN 978-3-030-98794-7 [contents] - [d17]Sebastiaan Brand, Thomas Bäck, Alfons Laarman:
FM 2023 Artefact for "A Decision Diagram Operation for Reachability". Zenodo, 2022 - [d16]Sander van Rijn, Sebastian Schmitt, Matthijs van Leeuwen, Thomas Bäck:
Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling: Generated data files and figures. Version v2. Zenodo, 2022 [all versions] - [d15]Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck:
Analyzing the Impact of Undersampling on the Benchmarkingand Configuration of Evolutionary Algorithms - Dataset. Zenodo, 2022 - [d14]Furong Ye, Diederick Vermetten, Carola Doerr, Thomas Bäck:
Data Sets for the study "Non-Elitist Selection Can Improve the Performance of Irace". Zenodo, 2022 - [i69]Furong Ye, Diederick L. Vermetten, Carola Doerr, Thomas Bäck:
Non-Elitist Selection among Survivor Configurations can Improve the Performance of Irace. CoRR abs/2203.09227 (2022) - [i68]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) - [i67]Dominik Schröder, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points. CoRR abs/2204.06539 (2022) - [i66]Danny Weyns, Thomas Bäck, René Vidal, Xin Yao, Ahmed Nabil Belbachir:
The Vision of Self-Evolving Computing Systems. CoRR abs/2204.06825 (2022) - [i65]Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck:
Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms. CoRR abs/2204.09353 (2022) - [i64]Andrea Skolik, Michele Cattelan, Sheir Yarkoni, Thomas Bäck, Vedran Dunjko:
Equivariant quantum circuits for learning on weighted graphs. CoRR abs/2205.06109 (2022) - [i63]Charles Moussa, Jan N. van Rijn, Thomas Bäck, Vedran Dunjko:
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets. CoRR abs/2206.09992 (2022) - [i62]David Von Dollen, Sheir Yarkoni, Daniel Weimer, Florian Neukart, Thomas Bäck:
Quantum-Enhanced Selection Operators for Evolutionary Algorithms. CoRR abs/2206.10743 (2022) - [i61]Patrick Echtenbruck, Martina Echtenbruck, Kees Joost Batenburg, Thomas Bäck, Boris Naujoks, Michael Emmerich:
Optimally Weighted Ensembles of Regression Models: Exact Weight Optimization and Applications. CoRR abs/2206.11263 (2022) - [i60]Yash J. Patel, Sofiène Jerbi, Thomas Bäck, Vedran Dunjko:
Reinforcement Learning Assisted Recursive QAOA. CoRR abs/2207.06294 (2022) - [i59]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) - [i58]Veysel Kocaman, Ofer M. Shir, Thomas Bäck, Ahmed Nabil Belbachir:
Saliency Can Be All You Need In Contrastive Self-Supervised Learning. CoRR abs/2210.16776 (2022) - [i57]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 abs/2211.07285 (2022) - [i56]Sebastiaan Brand, Thomas Bäck, Alfons Laarman:
A Decision Diagram Operation for Reachability. CoRR abs/2212.03684 (2022) - [i55]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
- [j42]Andrés Camero, Hao Wang, Enrique Alba, Thomas Bäck:
Bayesian neural architecture search using a training-free performance metric. Appl. Soft Comput. 106: 107356 (2021) - [j41]Markus Thill, Wolfgang Konen, Hao Wang, Thomas Bäck:
Temporal convolutional autoencoder for unsupervised anomaly detection in time series. Appl. Soft Comput. 112: 107751 (2021) - [j40]Anna V. Kononova, Fabio Caraffini, Thomas Bäck:
Differential evolution outside the box. Inf. Sci. 581: 587-604 (2021) - [j39]Yali Wang, Steffen Limmer, Markus Olhofer, Michael Emmerich, Thomas Bäck:
Automatic preference based multi-objective evolutionary algorithm on vehicle fleet maintenance scheduling optimization. Swarm Evol. Comput. 65: 100933 (2021) - [j38]Jianyong Sun, Xin Liu, Thomas Bäck, Zongben Xu:
Learning Adaptive Differential Evolution Algorithm From Optimization Experiences by Policy Gradient. IEEE Trans. Evol. Comput. 25(4): 666-680 (2021) - [c230]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 - [c229]Alexander Zeiser, Bas van Stein, Thomas Bäck:
Requirements towards optimizing analytics in industrial processes. ANT/EDI40 2021: 597-605 - [c228]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 - [c227]Van Duc Nguyen, Ewout Zwanenburg, Steffen Limmer, Wessel Luijben, Thomas Bäck, Markus Olhofer:
A Combination of Fourier Transform and Machine Learning for Fault Detection and Diagnosis of Induction Motors. DSA 2021: 344-351 - [c226]Duc Anh Nguyen, Jiawen Kong, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Anna V. Kononova, Thomas Bäck:
Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems. DSAA 2021: 1-9 - [c225]Roy de Winter, Bas van Stein, Thomas Bäck:
SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm. EMO 2021: 270-282 - [c224]Charles Moussa, Hao Wang, Henri Calandra, Thomas Bäck, Vedran Dunjko:
Tabu-Driven Quantum Neighborhood Samplers. EvoCOP 2021: 100-119 - [c223]Furong Ye, Carola Doerr, Thomas Bäck:
Leveraging benchmarking data for informed one-shot dynamic algorithm selection. GECCO Companion 2021: 245-246 - [c222]Jacob de Nobel, Hao Wang, Thomas Bäck:
Explorative data analysis of time series based algorithm features of CMA-ES variants. GECCO 2021: 510-518 - [c221]Alexander Hagg, Sebastian Berns, Alexander Asteroth, Simon Colton, Thomas Bäck:
Expressivity of parameterized and data-driven representations in quality diversity search. GECCO 2021: 678-686 - [c220]Ofer M. Shir, Thomas Bäck:
Sequential experimentation by evolutionary algorithms. GECCO Companion 2021: 941-958 - [c219]Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Is there anisotropy in structural bias? GECCO Companion 2021: 1243-1250 - [c218]Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
A new acquisition function for robust Bayesian optimization of unconstrained problems. GECCO Companion 2021: 1344-1345 - [c217]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: 1375-1384 - [c216]Anna V. Kononova, Ofer M. Shir, Teus Tukker, Pierluigi Frisco, Shutong Zeng, Thomas Bäck:
Addressing the multiplicity of solutions in optical lens design as a niching evolutionary algorithms computational challenge. GECCO Companion 2021: 1596-1604 - [c215]Sheir Yarkoni, Andreas Huck, Hanno Schülldorf, Benjamin Speitkamp, Marc Shakory Tabrizi, Martin Leib, Thomas Bäck, Florian Neukart:
Solving the Shipment Rerouting Problem with Quantum Optimization Techniques. ICCL 2021: 502-517 - [c214]Marios Kefalas, Mitra Baratchi, Asteris Apostolidis, Dirk van den Herik, Thomas Bäck:
Automated Machine Learning for Remaining Useful Life Estimation of Aircraft Engines. ICPHM 2021: 1-9 - [c213]Veysel Kocaman, Ofer M. Shir, Thomas Bäck:
The Unreasonable Effectiveness of the Final Batch Normalization Layer. ISVC (2) 2021: 81-93 - [c212]Gideon Hanse, Roy de Winter, Bas van Stein, Thomas Bäck:
Optimally Weighted Ensembles for Efficient Multi-objective Optimization. LOD 2021: 144-156 - [c211]Sheir Yarkoni, Alex Alekseyenko, Michael Streif, David Von Dollen, Florian Neukart, Thomas Bäck:
Multi-car paint shop optimization with quantum annealing. QCE 2021: 35-41 - [c210]Duc Anh Nguyen, Anna V. Kononova, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
Efficient AutoML via Combinational Sampling. SSCI 2021: 1-10 - [c209]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 - [e8]Thomas Bäck, Christian Wagner, Jonathan M. Garibaldi, H. K. Lam, Marie Cottrell, Juan Julián Merelo, Kevin Warwick:
Proceedings of the 13th International Joint Conference on Computational Intelligence, IJCCI 2021, Online Streaming, October 25-27, 2021. SCITEPRESS 2021, ISBN 978-989-758-534-0 [contents] - [d13]Sander van Rijn, Sebastian Schmitt, Matthijs van Leeuwen, Thomas Bäck:
Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling: Generated data files and figures. Version v1. Zenodo, 2021 [all versions] - [d12]Diederick Vermetten, Hao Wang, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer version 0.1.6.1 + example datasets. Zenodo, 2021 - [d11]Furong Ye, Carola Doerr, Thomas Bäck:
Data Sets for the study "Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection". Zenodo, 2021 - [d10]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Data sets for the study "Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance.". Zenodo, 2021 - [i54]Yali Wang, Steffen Limmer, Markus Olhofer, Michael Emmerich, Thomas Bäck:
Automatic Preference Based Multi-objective Evolutionary Algorithm on Vehicle Fleet Maintenance Scheduling Optimization. CoRR abs/2101.09556 (2021) - [i53]Jianyong Sun, Xin Liu, Thomas Bäck, Zongben Xu:
Learning adaptive differential evolution algorithm from optimization experiences by policy gradient. CoRR abs/2102.03572 (2021) - [i52]Furong Ye, Carola Doerr, Thomas Bäck:
Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection. CoRR abs/2102.06481 (2021) - [i51]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 abs/2102.12905 (2021) - [i50]Sander van Rijn, Sebastian Schmitt, Matthijs van Leeuwen, Thomas Bäck:
Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling. CoRR abs/2103.03280 (2021) - [i49]Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck, Nan Pu, Wei Chen, Michael S. Lew:
PREPRINT: Comparison of deep learning and hand crafted features for mining simulation data. CoRR abs/2103.06552 (2021) - [i48]Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck, Wei Chen, Michael S. Lew:
Preprint: Norm Loss: An efficient yet effective regularization method for deep neural networks. CoRR abs/2103.06583 (2021) - [i47]Hugo Manuel Proença, Thomas Bäck, Matthijs van Leeuwen:
Robust subgroup discovery. CoRR abs/2103.13686 (2021) - [i46]David Von Dollen, Florian Neukart, Daniel Weimer, Thomas Bäck:
Quantum-Assisted Feature Selection for Vehicle Price Prediction Modeling. CoRR abs/2104.04049 (2021) - [i45]Jacob de Nobel, Hao Wang, Thomas Bäck:
Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants. CoRR abs/2104.08098 (2021) - [i44]Alexander Hagg, Sebastian Berns, Alexander Asteroth, Simon Colton, Thomas Bäck:
Expressivity of Parameterized and Data-driven Representations in Quality Diversity Search. CoRR abs/2105.04247 (2021) - [i43]Alexander Hagg, Mike Preuss, Alexander Asteroth, Thomas Bäck:
An Analysis of Phenotypic Diversity in Multi-Solution Optimization. CoRR abs/2105.04252 (2021) - [i42]Alexander Hagg, Dominik Wilde, Alexander Asteroth, Thomas Bäck:
Designing Air Flow with Surrogate-assisted Phenotypic Niching. CoRR abs/2105.04256 (2021) - [i41]Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Is there Anisotropy in Structural Bias? CoRR abs/2105.04480 (2021) - [i40]Anna V. Kononova, Ofer M. Shir, Teus Tukker, Pierluigi Frisco, Shutong Zeng, Thomas Bäck:
Addressing the Multiplicity of Solutions in Optical Lens Design as a Niching Evolutionary Algorithms Computational Challenge. CoRR abs/2105.10541 (2021) - [i39]Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. CoRR abs/2106.06304 (2021) - [i38]Annie Wong, Thomas Bäck, Anna V. Kononova, Aske Plaat:
Multiagent Deep Reinforcement Learning: Challenges and Directions Towards Human-Like Approaches. CoRR abs/2106.15691 (2021) - [i37]Danny Weyns, Thomas Bäck, René Vidal, Xin Yao, Ahmed Nabil Belbachir:
Lifelong Computing. CoRR abs/2108.08802 (2021) - [i36]Sheir Yarkoni, Alex Alekseyenko, Michael Streif, David Von Dollen, Florian Neukart, Thomas Bäck:
Multi-car paint shop optimization with quantum annealing. CoRR abs/2109.07876 (2021) - [i35]Veysel Kocaman, Ofer M. Shir, Thomas Bäck:
The Unreasonable Effectiveness of the Final Batch Normalization Layer. CoRR abs/2109.09016 (2021) - [i34]Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. CoRR abs/2111.04077 (2021) - 2020
- [j37]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) - [j36]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking discrete optimization heuristics with IOHprofiler. Appl. Soft Comput. 88: 106027 (2020) - [j35]Mozhan Soltani, Felienne Hermans, Thomas Bäck:
The significance of bug report elements. Empir. Softw. Eng. 25(6): 5255-5294 (2020) - [c208]Marios Kefalas, Milan Koch, Victor Geraedts, Hao Wang, Martijn Tannemaat, Thomas Bäck:
Automated Machine Learning for the Classification of Normal and Abnormal Electromyography Data. IEEE BigData 2020: 1176-1185 - [c207]Alexander Hagg, Mike Preuss, Alexander Asteroth, Thomas Bäck:
An Analysis of Phenotypic Diversity in Multi-solution Optimization. BIOMA 2020: 43-55 - [c206]Markus Thill, Wolfgang Konen, Thomas Bäck:
Time Series Encodings with Temporal Convolutional Networks. BIOMA 2020: 161-173 - [c205]Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Can Single Solution Optimisation Methods Be Structurally Biased? CEC 2020: 1-9 - [c204]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 - [c203]Diederick Vermetten, Hao Wang, Thomas Bäck, Carola Doerr:
Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. GECCO 2020: 654-662 - [c202]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. GECCO 2020: 903-912 - [c201]Ofer M. Shir, Thomas Bäck:
Sequential experimentation by evolutionary algorithms. GECCO Companion 2020: 957-974 - [c200]Hao Wang, Carola Doerr, Ofer M. Shir, Thomas Bäck:
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion 2020: 1043-1054 - [c199]Rick Boks, Hao Wang, Thomas Bäck:
A modular hybridization of particle swarm optimization and differential evolution. GECCO Companion 2020: 1418-1425 - [c198]Alexander Hagg, Alexander Asteroth, Thomas Bäck:
A Deep Dive Into Exploring the Preference Hypervolume. ICCC 2020: 394-397 - [c197]Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck, Nan Pu, Wei Chen, Michael S. Lew:
Comparison of deep learning and hand crafted features for mining simulation data. ICPR 2020: 3396-3403 - [c196]Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck, Wei Chen, Michael S. Lew:
Norm Loss: An efficient yet effective regularization method for deep neural networks. ICPR 2020: 8812-8818 - [c195]Veysel Kocaman, Ofer M. Shir, Thomas Bäck:
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study. ICPR 2020: 10404-10411 - [c194]Thiago Rios, Bas van Stein, Stefan Menzel, Thomas Bäck, Bernhard Sendhoff, Patricia Wollstadt:
Feature Visualization for 3D Point Cloud Autoencoders. IJCNN 2020: 1-9 - [c193]Ullah Ullah, Zhao Xu, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models. IJCNN 2020: 1-9 - [c192]Zhengtian Ai, Ingo Heinle, Christian Schelske, Hao Wang, Peter Krause, Thomas Bäck:
A Classification-based Solution For Recommending Process Parameters of Production Processes Without Quality Measures. ISM 2020: 600-607 - [c191]Jiawen Kong, Thiago Rios, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck:
On the Performance of Oversampling Techniques for Class Imbalance Problems. PAKDD (2) 2020: 84-96 - [c190]Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen:
Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL. ECML/PKDD (1) 2020: 19-35 - [c189]Alexander Hagg, Dominik Wilde, Alexander Asteroth, Thomas Bäck:
Designing Air Flow with Surrogate-Assisted Phenotypic Niching. PPSN (1) 2020: 140-153 - [c188]Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Can Compact Optimisation Algorithms Be Structurally Biased? PPSN (1) 2020: 229-242 - [c187]Yali Wang, André H. Deutz, Thomas Bäck, Michael Emmerich:
Improving Many-Objective Evolutionary Algorithms by Means of Edge-Rotated Cones. PPSN (2) 2020: 313-326 - [c186]Jiawen Kong, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck:
Improving Imbalanced Classification by Anomaly Detection. PPSN (1) 2020: 512-523 - [c185]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. PPSN (2) 2020: 699-713 - [c184]Yali Wang, André H. Deutz, Thomas Bäck, Michael Emmerich:
Edge-Rotated Cone Orders in Multi-objective Evolutionary Algorithms for Improved Convergence and Preference Articulation. SSCI 2020: 165-172 - [c183]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 - [c182]Raphael Patrick Prager, Heike Trautmann, Hao Wang, Thomas Bäck, Pascal Kerschke:
Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. SSCI 2020: 996-1003 - [c181]Bas van Stein, Hao Wang, Thomas Bäck:
Neural Network Design: Learning from Neural Architecture Search. SSCI 2020: 1341-1349 - [c180]Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich:
A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling. SSCI 2020: 2746-2753 - [c179]Sibghat Ullah, Duc Anh Nguyen, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
Exploring Dimensionality Reduction Techniques for Efficient Surrogate-Assisted optimization. SSCI 2020: 2965-2974 - [c178]Milan Koch, Hao Wang, Robert Bürgel, Thomas Bäck:
Towards Data-driven Services in Vehicles. VEHITS 2020: 45-52 - [e7]Juan Julián Merelo Guervós, Jonathan M. Garibaldi, Christian Wagner, Thomas Bäck, Kurosh Madani, Kevin Warwick:
Proceedings of the 12th International Joint Conference on Computational Intelligence, IJCCI 2020, Budapest, Hungary, November 2-4, 2020. SCITEPRESS 2020, ISBN 978-989-758-475-6 [contents] - [e6]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12269, Springer 2020, ISBN 978-3-030-58111-4 [contents] - [e5]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12270, Springer 2020, ISBN 978-3-030-58114-5 [contents] - [d9]Rick Boks, Hao Wang, Thomas Bäck:
Experimental Results for the study "A Modular Hybridization of Particle Swarm Optimization and Differential Evolution". Zenodo, 2020 - [d8]Jiawen Kong, Wojtek Kowalczyk, Duc Anh Nguyen, Stefan Menzel, Thomas Bäck:
Hyperparameter Optimisation for Improving Classification under Class Imbalance. Zenodo, 2020 - [d7]Jiawen Kong, Thiago Rios, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck:
On the Performance of Oversampling Techniques for Class Imbalance Problems. Zenodo, 2020 - [d6]Markus Thill, Wolfgang Konen, Thomas Bäck:
MarkusThill/MGAB: The Mackey-Glass Anomaly Benchmark. Version v1.0.0. Zenodo, 2020 [all versions] - [d5]Markus Thill, Wolfgang Konen, Thomas Bäck:
MarkusThill/MGAB: The Mackey-Glass Anomaly Benchmark. Version v1.0.1. Zenodo, 2020 [all versions] - [d4]Sibghat Ullah, Hao Wang, Stefan Menzel, Thomas Bäck, Bernhard Sendhoff:
An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization. Zenodo, 2020 - [d3]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
The Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm withConfigurable Crossover Probability". Version 1. Zenodo, 2020 [all versions] - [d2]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". Version 2. Zenodo, 2020 [all versions] - [d1]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". Version 3. Zenodo, 2020 [all versions] - [i33]Andrés Camero, Hao Wang, Enrique Alba, Thomas Bäck:
Bayesian Neural Architecture Search using A Training-Free Performance Metric. CoRR abs/2001.10726 (2020) - [i32]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm versus Column Generation Method. CoRR abs/2003.03792 (2020) - [i31]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
AirCROP: Airline Crew Pairing Optimizer for Complex Flight Networks Involving Multiple Crew Bases & Billion-Plus Variables. CoRR abs/2003.03994 (2020) - [i30]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
On Initializing Airline Crew Pairing Optimization for Large-scale Complex Flight Networks. CoRR abs/2003.06423 (2020) - [i29]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) - [i28]Yali Wang, André H. Deutz, Thomas Bäck, Michael T. M. Emmerich:
Improving Many-objective Evolutionary Algorithms by Means of Expanded Cone Orders. CoRR abs/2004.06941 (2020) - [i27]Anna V. Kononova, Fabio Caraffini, Thomas Bäck:
Differential evolution outside the box. CoRR abs/2004.10489 (2020) - [i26]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
A Novel Column Generation Heuristic for Airline Crew Pairing Optimization with Large-scale Complex Flight Networks. CoRR abs/2005.08636 (2020) - [i25]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Benchmarking a $(μ+λ)$ Genetic Algorithm with Configurable Crossover Probability. CoRR abs/2006.05889 (2020) - [i24]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case. CoRR abs/2006.06586 (2020) - [i23]Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen:
Discovering outstanding subgroup lists for numeric targets using MDL. CoRR abs/2006.09186 (2020) - [i22]Rick Boks, Hao Wang, Thomas Bäck:
A Modular Hybridization of Particle Swarm Optimization and Differential Evolution. CoRR abs/2006.11886 (2020) - [i21]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. CoRR abs/2007.03953 (2020) - [i20]Bas van Stein, Hao Wang, Thomas Bäck:
Neural Network Design: Learning from Neural Architecture Search. CoRR abs/2011.00521 (2020) - [i19]Veysel Kocaman, Ofer M. Shir, Thomas Bäck:
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study. CoRR abs/2011.06319 (2020)
2010 – 2019
- 2019
- [j34]Hao Wang, Michael Emmerich, Thomas Bäck:
Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies. Evol. Comput. 27(4): 699-725 (2019) - [j33]Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Efficient computation of expected hypervolume improvement using box decomposition algorithms. J. Glob. Optim. 75(1): 3-34 (2019) - [j32]Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient. Swarm Evol. Comput. 44: 945-956 (2019) - [c177]Milan Koch, Victor Geraedts, Hao Wang, Martijn Tannemaat, Thomas Bäck:
Automated Machine Learning for EEG-Based Classification of Parkinson's Disease Patients. IEEE BigData 2019: 4845-4852 - [c176]Yali Wang, Steffen Limmer, Markus Olhofer, Michael T. M. Emmerich, Thomas Bäck:
Vehicle Fleet Maintenance Scheduling Optimization by Multi-objective Evolutionary Algorithms. CEC 2019: 442-449 - [c175]Furong Ye, Carola Doerr, Thomas Bäck:
Interpolating Local and Global Search by Controlling the Variance of Standard Bit Mutation. CEC 2019: 2292-2299 - [c174]Hao Wang, Yitan Lou, Thomas Bäck:
Hyper-Parameter Optimization for Improving the Performance of Grammatical Evolution. CEC 2019: 2649-2656 - [c173]Yali Wang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Diversity-Indicator Based Multi-Objective Evolutionary Algorithm: DI-MOEA. EMO 2019: 346-358 - [c172]Alexander Hagg, Alexander Asteroth, Thomas Bäck:
Modeling user selection in quality diversity. GECCO 2019: 116-124 - [c171]Hao Wang, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss:
On the potential of evolution strategies for neural network weight optimization. GECCO (Companion) 2019: 191-192 - [c170]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
Solving optimization problems with high conditioning by means of online whitening. GECCO (Companion) 2019: 243-244 - [c169]Naama Horesh, Thomas Bäck, Ofer M. Shir:
Predict or screen your expensive assay: DoE vs. surrogates in experimental combinatorial optimization. GECCO 2019: 274-284 - [c168]Pierluigi Frisco, Timo Bootsma, Thomas Bäck:
Multi-objective genetic algorithms for reducing mark read-out effort in lithographic tests. GECCO (Companion) 2019: 365-366 - [c167]Kaifeng Yang, Pramudita Satria Palar, Michael Emmerich, Koji Shimoyama, Thomas Bäck:
A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization. GECCO 2019: 656-663 - [c166]Diederick Vermetten, Sander van Rijn, Thomas Bäck, Carola Doerr:
Online selection of CMA-ES variants. GECCO 2019: 951-959 - [c165]Ofer M. Shir, Thomas Bäck:
Sequential experimentation by evolutionary algorithms. GECCO (Companion) 2019: 1095-1112 - [c164]Marios Kefalas, Steffen Limmer, Asteris Apostolidis, Markus Olhofer, Michael Emmerich, Thomas Bäck:
A tabu search-based memetic algorithm for the multi-objective flexible job shop scheduling problem. GECCO (Companion) 2019: 1254-1262 - [c163]Borja Calvo, Ofer M. Shir, Josu Ceberio, Carola Doerr, Hao Wang, Thomas Bäck, José Antonio Lozano:
Bayesian performance analysis for black-box optimization benchmarking. GECCO (Companion) 2019: 1789-1797 - [c162]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking discrete optimization heuristics with IOHprofiler. GECCO (Companion) 2019: 1798-1806 - [c161]Sneha Saha, Thiago Rios, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck, Xin Yao, Zhao Xu, Patricia Wollstadt:
Learning Time-Series Data of Industrial Design Optimization using Recurrent Neural Networks. ICDM Workshops 2019: 785-792 - [c160]Bas van Stein, Hao Wang, Thomas Bäck:
Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization. IJCNN 2019: 1-7 - [c159]Sina Däubener, Sebastian Schmitt, Hao Wang, Peter Krause, Thomas Bäck:
Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms. ICDM 2019: 161-175 - [c158]Markus Thill, Sina Däubener, Wolfgang Konen, Thomas Bäck:
Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks. ITAT 2019: 17-25 - [c157]Can Wang, Thomas Bäck, Holger H. Hoos, Mitra Baratchi, Steffen Limmer, Markus Olhofer:
Automated Machine Learning for Short-term Electric Load Forecasting. SSCI 2019: 314-321 - [c156]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 - [c155]Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization. SSCI 2019: 819-828 - [c154]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 - [c153]Xin Guo, Bas van Stein, Thomas Bäck:
A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem. SSCI 2019: 2042-2049 - [c152]Teddy Etoeharnowo, Koen Castelein, Hao Wang, Thomas Bäck:
Switching Between Swarm Optimization Algorithms During a Run: An Empirical Study. SSCI 2019: 2295-2302 - [c151]Jiawen Kong, Wojtek Kowalczyk, Duc Anh Nguyen, Thomas Bäck, Stefan Menzel:
Hyperparameter Optimisation for Improving Classification under Class Imbalance. SSCI 2019: 3072-3078 - [i18]Furong Ye, Carola Doerr, Thomas Bäck:
Interpolating Local and Global Search by Controlling the Variance of Standard Bit Mutation. CoRR abs/1901.05573 (2019) - [i17]Diederick Vermetten, Sander van Rijn, Thomas Bäck, Carola Doerr:
Online Selection of CMA-ES Variants. CoRR abs/1904.07801 (2019) - [i16]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning. CoRR abs/1904.08397 (2019) - [i15]Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Efficient Computation of Expected Hypervolume Improvement Using Box Decomposition Algorithms. CoRR abs/1904.12672 (2019) - [i14]Alexander Hagg, Alexander Asteroth, Thomas Bäck:
Modeling User Selection in Quality Diversity. CoRR abs/1907.06912 (2019) - [i13]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. CoRR abs/1912.05899 (2019) - [i12]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking Discrete Optimization Heuristics with IOHprofiler. CoRR abs/1912.09237 (2019) - 2018
- [c150]Hao Wang, Michael Emmerich, Thomas Bäck:
Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization. CEC 2018: 1-8 - [c149]Sheir Yarkoni, Aske Plaat, Thomas Bäck:
First Results Solving Arbitrarily Structured Maximum Independent Set Problems Using Quantum Annealing. CEC 2018: 1-6 - [c148]Thomas Bäck:
Algorithms for Simulation-Based Optimization Problems. ECMS 2018: 5-7 - [c147]Koen van der Blom, Thomas Bäck:
A new foraging-based algorithm for online scheduling. GECCO 2018: 53-60 - [c146]Sander van Rijn, Sebastian Schmitt, Markus Olhofer, Matthijs van Leeuwen, Thomas Bäck:
Multi-fidelity surrogate model approach to optimization. GECCO (Companion) 2018: 225-226 - [c145]Hao Wang, Thomas Bäck:
Ranking empirical cumulative distribution functions using stochastic and pareto dominance. GECCO (Companion) 2018: 257-258 - [c144]Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck:
Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones. GECCO 2018: 951-958 - [c143]Ofer M. Shir, Thomas Bäck:
Sequential experimentation by evolutionary algorithms. GECCO (Companion) 2018: 956-976 - [c142]Pramudita Satria Palar, Kaifeng Yang, Koji Shimoyama, Michael Emmerich, Thomas Bäck:
Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement. GECCO 2018: 1333-1340 - [c141]Ofer M. Shir, Carola Doerr, Thomas Bäck:
Compiling a benchmarking test-suite for combinatorial black-box optimization: a position paper. GECCO (Companion) 2018: 1753-1760 - [c140]Milan Koch, Hao Wang, Thomas Bäck:
Machine Learning for Predicting the Damaged Parts of a Low Speed Vehicle Crash. ICDIM 2018: 179-184 - [c139]Milan Koch, Thomas Bäck:
Machine Learning for Predicting the Impact Point of a Low Speed Vehicle Crash. ICMLA 2018: 1432-1437 - [c138]Theodoros Georgiou, Sebastian Schmitt, Markus Olhofer, Yu Liu, Thomas Bäck, Michael S. Lew:
Learning Fluid Flows. IJCNN 2018: 1-8 - [c137]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck:
A Novel Uncertainty Quantification Method for Efficient Global Optimization. IPMU (3) 2018: 480-491 - [c136]Roy de Winter, Bas van Stein, Matthys Dijkman, Thomas Bäck:
Designing Ships Using Constrained Multi-objective Efficient Global Optimization. LOD 2018: 191-203 - [c135]Sander van Rijn, Carola Doerr, Thomas Bäck:
Towards an Adaptive CMA-ES Configurator. PPSN (1) 2018: 54-65 - [c134]Alexander Hagg, Alexander Asteroth, Thomas Bäck:
Prototype Discovery Using Quality-Diversity. PPSN (1) 2018: 500-511 - [c133]Hugo Manuel Proença, Ruben Klijn, Thomas Bäck, Matthijs van Leeuwen:
Identifying flight delay patterns using diverse subgroup discovery. SSCI 2018: 60-67 - [i11]Alexander Hagg, Alexander Asteroth, Thomas Bäck:
Prototype Discovery using Quality-Diversity. CoRR abs/1807.09488 (2018) - [i10]Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck:
Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling (1+λ) EA Variants on OneMax and LeadingOnes. CoRR abs/1808.05850 (2018) - [i9]Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, Thomas Bäck:
IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. CoRR abs/1810.05281 (2018) - [i8]Bas van Stein, Hao Wang, Thomas Bäck:
Automatic Configuration of Deep Neural Networks with EGO. CoRR abs/1810.05526 (2018) - 2017
- [j31]Samineh Bagheri, Wolfgang Konen, Michael Emmerich, Thomas Bäck:
Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets. Appl. Soft Comput. 61: 377-393 (2017) - [j30]Jiaqi Zhao, Vitor Basto-Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Ke Tang, Michael T. M. Emmerich:
Corrigendum to 'Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms' [Information Sciences volumes 367-368 (2016) 80-104]. Inf. Sci. 403: 55 (2017) - [j29]Zhiwei Yang, Jan-Paul van Osta, Barry D. Van Veen, Rick van Krevelen, Richard van Klaveren, Andries Stam, Joost N. Kok, Thomas Bäck, Michael Emmerich:
Dynamic vehicle routing with time windows in theory and practice. Nat. Comput. 16(1): 119-134 (2017) - [c132]Koen van der Blom, Sjonnie Boonstra, Hèrm Hofmeyer, Thomas Bäck, Michael T. M. Emmerich:
Configuring advanced evolutionary algorithms for multicriteria building spatial design optimisation. CEC 2017: 1803-1810 - [c131]Markus Thill, Wolfgang Konen, Thomas Bäck:
Online anomaly detection on the webscope S5 dataset: A comparative study. EAIS 2017: 1-8 - [c130]Hao Wang, André H. Deutz, Thomas Bäck, Michael Emmerich:
Hypervolume Indicator Gradient Ascent Multi-objective Optimization. EMO 2017: 654-669 - [c129]Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck:
Algorithm configuration data mining for CMA evolution strategies. GECCO 2017: 737-744 - [c128]Ofer M. Shir, Thomas Bäck, Joshua D. Knowles, Richard Allmendinger:
Sequential experimentation by evolutionary algorithms. GECCO (Companion) 2017: 828-851 - [c127]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 - [c126]Marco Schönfelder, Valentin Protschky, Thomas Bäck:
Reconstructing fixed time traffic light cycles by camera data analytics. ITSC 2017: 1-7 - [c125]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 - [c124]Sheir Yarkoni, Hao Wang, Aske Plaat, Thomas Bäck:
Boosting Quantum Annealing Performance Using Evolution Strategies for Annealing Offsets Tuning. QTOP@NetSys 2017: 157-168 - [c123]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 - [i7]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) - [i6]Martin Hofmann, Florian Neukart, Thomas Bäck:
Artificial Intelligence and Data Science in the Automotive Industry. CoRR abs/1709.01989 (2017) - 2016
- [j28]Zhiwei Yang, Michael Emmerich, Thomas Bäck, Joost N. Kok:
Multi-objective inventory routing with uncertain demand using population-based metaheuristics. Integr. Comput. Aided Eng. 23(3): 205-220 (2016) - [j27]Jiaqi Zhao, Vitor Basto-Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Ke Tang, Michael T. M. Emmerich:
Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms. Inf. Sci. 367-368: 80-104 (2016) - [c122]Bas van Stein, Matthijs van Leeuwen, Thomas Bäck:
Local subspace-based outlier detection using global neighbourhoods. IEEE BigData 2016: 1136-1142 - [c121]Hao Wang, Michael T. M. Emmerich, Thomas Bäck:
Balancing risk and expected gain in kriging-based global optimization. CEC 2016: 719-727 - [c120]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
Equality constraint handling for surrogate-assisted constrained optimization. CEC 2016: 1924-1931 - [c119]Kaifeng Yang, André H. Deutz, Zhiwei Yang, Thomas Bäck, Michael T. M. Emmerich:
Truncated expected hypervolume improvement: Exact computation and application. CEC 2016: 4350-4357 - [c118]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 - [c117]Maren Urselmann, Christophe Foussette, Tim Janus, Stephen Tlatlik, Axel Gottschalk, Michael T. M. Emmerich, Sebastian Engell, Thomas Bäck:
Selection of a DFO Method for the Efficient Solution of Continuous Constrained Sub-Problems within a Memetic Algorithm for Chemical Process Synthesis. GECCO 2016: 1029-1036 - [c116]Kaifeng Yang, Longmei Li, André H. Deutz, Thomas Bäck, Michael Emmerich:
Preference-based multiobjective optimization using truncated expected hypervolume improvement. ICNC-FSKD 2016: 276-281 - [c115]Zhiwei Yang, Hao Wang, Kaifeng Yang, Thomas Bäck, Michael Emmerich:
SMS-EMOA with multiple dynamic reference points. ICNC-FSKD 2016: 282-288 - [c114]Bas van Stein, Wojtek Kowalczyk, Thomas Bäck:
Analysis and Visualization of Missing Value Patterns. IPMU (2) 2016: 187-198 - [c113]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
Online selection of surrogate models for constrained black-box optimization. SSCI 2016: 1-8 - [c112]Pepijn Van Heiningen, Bas van Stein, Thomas Bäck:
A framework for evaluating meta-models for simulation-based optimisation. SSCI 2016: 1-8 - [c111]Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck:
Evolving the structure of Evolution Strategies. SSCI 2016: 1-8 - [i5]Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck:
Evolving the Structure of Evolution Strategies. CoRR abs/1610.05231 (2016) - [i4]Bas van Stein, Matthijs van Leeuwen, Thomas Bäck:
Local Subspace-Based Outlier Detection using Global Neighbourhoods. CoRR abs/1611.00183 (2016) - 2015
- [j26]Patrick Koch, Tobias Wagner, Michael T. M. Emmerich, Thomas Bäck, Wolfgang Konen:
Efficient multi-criteria optimization on noisy machine learning problems. Appl. Soft Comput. 29: 357-370 (2015) - [j25]Pu Wang, Michael Emmerich, Rui Li, Ke Tang, Thomas Bäck, Xin Yao:
Convex Hull-Based Multiobjective Genetic Programming for Maximizing Receiver Operating Characteristic Performance. IEEE Trans. Evol. Comput. 19(2): 188-200 (2015) - [c110]Sander van Rijn, Michael T. M. Emmerich, Edgar Reehuis, Thomas Bäck:
Optimizing Highly Constrained Truck Loadings Using a Self-Adaptive Genetic Algorithm. CEC 2015: 227-234 - [c109]Joost Leuven, Michael Emmerich, Edgar Reehuis, Thomas Bäck:
User-derived mutation in highly constrained Truck Loading Optimization. CEC 2015: 235-242 - [c108]Kaifeng Yang, Daniel Gaida, Thomas Bäck, Michael Emmerich:
Expected hypervolume improvement algorithm for PID controller tuning and the multiobjective dynamical control of a biogas plant. CEC 2015: 1934-1942 - [c107]Zhiwei Yang, Michael Emmerich, Thomas Bäck:
Ant based solver for dynamic vehicle routing problem with time windows and multiple priorities. CEC 2015: 2813-2819 - [c106]Xiaoke Zhang, Jun Wu, Cuiying Duan, Michael T. M. Emmerich, Thomas Bäck:
Towards robustness optimization of complex networks based on redundancy backup. CEC 2015: 2820-2826 - [c105]Asep Maulana, Zhongzhou Jiang, Jing Liu, Thomas Bäck, Michael T. M. Emmerich:
Reducing complexity in many objective optimization using community detection. CEC 2015: 3140-3147 - [c104]Hao Wang, Thomas Bäck, Michael T. M. Emmerich:
Multi-point Efficient Global Optimization Using Niching Evolution Strategy. EVOLVE 2015: 146-162 - [c103]Patrick Koch, Samineh Bagheri, Wolfgang Konen, Christophe Foussette, Peter Krause, Thomas Bäck:
A New Repair Method For Constrained Optimization. GECCO 2015: 273-280 - [c102]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich:
Optimally Weighted Cluster Kriging for Big Data Regression. IDA 2015: 310-321 - [c101]Zhiwei Yang, Michael Emmerich, Thomas Bäck, Joost N. Kok:
Multicriteria Inventory Routing by Cooperative Swarms and Evolutionary Algorithms. IWINAC (2) 2015: 127-137 - [c100]Pepijn Van Heiningen, Edgar Reehuis, Thomas Bäck:
Comparing a Weiszfeld's-Based Procedure and (1+1)-es for Solving the Planar Single-Facility Location-Routing Problem. SSCI 2015: 1743-1750 - [i3]Samineh Bagheri, Wolfgang Konen, Michael Emmerich, Thomas Bäck:
Solving the G-problems in less than 500 iterations: Improved efficient constrained optimization by surrogate modeling and adaptive parameter control. CoRR abs/1512.09251 (2015) - 2014
- [c99]Thomas Bäck:
Introduction to evolution strategies. GECCO (Companion) 2014: 251-280 - [c98]Kaifeng Yang, Michael T. M. Emmerich, Rui Li, Ji Wang, Thomas Bäck:
Power Distribution Network Reconfiguration by Evolutionary Integer Programming. PPSN 2014: 11-23 - [c97]Hao Wang, Michael Emmerich, Thomas Bäck:
Mirrored orthogonal sampling with pairwise selection in evolution strategies. SAC 2014: 154-156 - [i2]Jiaqi Zhao, Vitor Basto-Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Michael T. M. Emmerich:
Multiobjective Optimization of Classifiers by Means of 3-D Convex Hull Based Evolutionary Algorithm. CoRR abs/1412.5710 (2014) - 2013
- [b3]Thomas Bäck, Christophe Foussette, Peter Krause:
Contemporary Evolution Strategies. Natural Computing Series, Springer 2013, ISBN 978-3-642-40136-7, pp. 1-86 - [j24]Rui Li, Michael T. M. Emmerich, Jeroen Eggermont, Thomas Bäck, Martin Schütz, Jouke Dijkstra, Johan H. C. Reiber:
Mixed Integer Evolution Strategies for Parameter Optimization. Evol. Comput. 21(1): 29-64 (2013) - [c96]Christoph Johann Stettina, Zhao Zhou, Thomas Bäck, Bernhard R. Katzy:
Academic education of software engineering practices: towards planning and improving capstone courses based upon intensive coaching and team routines. CSEE&T 2013: 169-178 - [c95]Thomas Bäck:
Evolution strategies: basic introduction. GECCO (Companion) 2013: 265-292 - [c94]Edgar Reehuis, Markus Olhofer, Michael Emmerich, Bernhard Sendhoff, Thomas Bäck:
Novelty and interestingness measures for design-space exploration. GECCO 2013: 1541-1548 - [c93]Edgar Reehuis, Markus Olhofer, Bernhard Sendhoff, Thomas Bäck:
Learning-Guided Exploration in Airfoil Optimization. IDEAL 2013: 505-512 - [c92]Barry D. Van Veen, Michael Emmerich, Zhiwei Yang, Thomas Bäck, Joost N. Kok:
Ant Colony Algorithms for the Dynamic Vehicle Routing Problem with Time Windows. IWINAC (2) 2013: 1-10 - [i1]Pu Wang, Michael Emmerich, Rui Li, Ke Tang, Thomas Bäck, Xin Yao:
Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance. CoRR abs/1303.3145 (2013) - 2012
- [c91]Stefan Wink, Thomas Bäck, Michael T. M. Emmerich:
A meta-genetic algorithm for solving the Capacitated Vehicle Routing Problem. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c90]Thomas Bäck:
Evolution strategies: basic introduction. GECCO (Companion) 2012: 711-736 - [c89]Jelle de Groot, Ariadi Nugroho, Thomas Bäck, Joost Visser:
What is the value of your software? MTD@ICSE 2012: 37-44 - [e4]Grzegorz Rozenberg, Thomas Bäck, Joost N. Kok:
Handbook of Natural Computing. Springer 2012, ISBN 978-3-540-92909-3 [contents] - 2011
- [c88]Thomas Bäck:
Evolution strategies: basic introduction. GECCO (Companion) 2011: 875-898 - [c87]Johannes W. Kruisselbrink, Edgar Reehuis, André H. Deutz, Thomas Bäck, Michael Emmerich:
Using the uncertainty handling CMA-ES for finding robust optima. GECCO 2011: 877-884 - [c86]Johannes W. Kruisselbrink, Rui Li, Edgar Reehuis, Jeroen Eggermont, Thomas Bäck:
On the log-normal self-adaptation of the mutation rate in binary search spaces. GECCO 2011: 893-900 - [c85]Thomas Bäck, Lutz Keßler, Ingo Heinle:
Evolutionary strategies for identification and validation of material model parameters for forming simulations. GECCO 2011: 1779-1786 - 2010
- [j23]Ofer M. Shir, Michael Emmerich, Thomas Bäck:
Adaptive Niche Radii and Niche Shapes Approaches for Niching with the CMA-ES. Evol. Comput. 18(1): 97-126 (2010) - [c84]Johannes W. Kruisselbrink, Michael T. M. Emmerich, André H. Deutz, Thomas Bäck:
A robust optimization approach using Kriging metamodels for robustness approximation in the CMA-ES. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c83]Edgar Reehuis, Thomas Bäck:
Mixed-integer evolution strategy using multiobjective selection applied to warehouse design optimization. GECCO 2010: 1187-1194 - [c82]Thomas Bäck:
Evolution strategies: basic introduction. GECCO (Companion) 2010: 2263-2288 - [c81]Thomas Bäck, Joshua D. Knowles, Ofer M. Shir:
Experimental optimization by evolutionary algorithms. GECCO (Companion) 2010: 2897-2916 - [c80]Johannes W. Kruisselbrink, Michael Emmerich, André H. Deutz, Thomas Bäck:
Exploiting Overlap When Searching for Robust Optima. PPSN (1) 2010: 63-72 - [c79]Johannes W. Kruisselbrink, Michael Emmerich, Thomas Bäck:
An Archive Maintenance Scheme for Finding Robust Solutions. PPSN (1) 2010: 214-223
2000 – 2009
- 2009
- [j22]Ofer M. Shir, Thomas Bäck:
Niching with derandomized evolution strategies in artificial and real-world landscapes. Nat. Comput. 8(1): 171-196 (2009) - [c78]Ofer M. Shir, Thomas Bäck:
Niching Methods: Speciation Theory Applied for Multi-modal Function Optimization. Algorithmic Bioprocesses 2009: 705-729 - [c77]Johannes W. Kruisselbrink, Michael T. M. Emmerich, Thomas Bäck, Andreas Bender, Adriaan P. IJzerman, Eelke van der Horst:
Combining Aggregation with Pareto Optimization: A Case Study in Evolutionary Molecular Design. EMO 2009: 453-467 - [c76]Johannes W. Kruisselbrink, Alexander Aleman, Michael T. M. Emmerich, Adriaan P. IJzerman, Andreas Bender, Thomas Bäck, Eelke van der Horst:
Enhancing search space diversity in multi-objective evolutionary drug molecule design using niching. GECCO 2009: 217-224 - [c75]Johannes W. Kruisselbrink, Michael T. M. Emmerich, Thomas Bäck:
On the limitations of adaptive resampling in using the student's t-test evolution strategies. GECCO (Companion) 2009: 2649-2656 - [c74]Juan Chen, Michael T. M. Emmerich, Rui Li, Joost N. Kok, Thomas Bäck:
How to Do Recombination in Evolution Strategies: An Empirical Study. IWINAC (1) 2009: 223-232 - 2008
- [j21]Thomas Bäck, Michael Emmerich, Ofer M. Shir:
Evolutionary algorithms for real world applications [Application Notes]. IEEE Comput. Intell. Mag. 3(1): 64-67 (2008) - [c73]Ofer M. Shir, Thomas Bäck, Herschel Rabitz, Marc J. J. Vrakking:
On the evolution of laser pulses under a dynamic Quantum Control environment. IEEE Congress on Evolutionary Computation 2008: 2127-2134 - [c72]Rui Li, Michael T. M. Emmerich, Jeroen Eggermont, Ernst G. P. Bovenkamp, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Metamodel-assisted mixed integer evolution strategies and their application to intravascular ultrasound image analysis. IEEE Congress on Evolutionary Computation 2008: 2764-2771 - [c71]Jeroen Eggermont, Rui Li, Ernst G. P. Bovenkamp, Henk A. Marquering, Michael T. M. Emmerich, Aad van der Lugt, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Optimizing Computed Tomographic Angiography Image Segmentation Using Fitness Based Partitioning. EvoWorkshops 2008: 275-284 - [c70]Ofer M. Shir, Jonathan Roslund, Thomas Bäck, Herschel Rabitz:
Performance analysis of derandomized evolution strategies in quantum control experiments. GECCO 2008: 519-526 - [c69]Ron Breukelaar, Thomas Bäck:
Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata. GECCO 2008: 1101-1102 - [c68]Johannes W. Kruisselbrink, Thomas Bäck, Adriaan P. IJzerman, Eelke van der Horst:
Evolutionary algorithms for automated drug design towards target molecule properties. GECCO 2008: 1555-1562 - [c67]Thomas Bäck:
Evolution strategies: basic introduction. GECCO (Companion) 2008: 2259-2276 - [c66]Jan Willem Klinkenberg, Michael T. M. Emmerich, André H. Deutz, Ofer M. Shir, Thomas Bäck:
A Reduced-Cost SMS-EMOA Using Kriging, Self-Adaptation, and Parallelization. MCDM 2008: 301-311 - [c65]Vincent van der Goes, Ofer M. Shir, Thomas Bäck:
Niche Radius Adaptation with Asymmetric Sharing. PPSN 2008: 195-204 - [c64]Rui Li, Jeroen Eggermont, Ofer M. Shir, Michael T. M. Emmerich, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Mixed-Integer Evolution Strategies with Dynamic Niching. PPSN 2008: 246-255 - 2007
- [j20]Christiaan V. Henkel, Thomas Bäck, Joost N. Kok, Grzegorz Rozenberg, Herman P. Spaink:
DNA computing of solutions to knapsack problems. Biosyst. 88(1-2): 156-162 (2007) - [j19]Thomas Bäck, Benedikt Löwe:
Computing and the natural sciences at CiE 2005. Theor. Comput. Sci. 371(1-2): 1-3 (2007) - [c63]Riccardo Fanciulli, Lars Willmes, Janne Savolainen, Peter van der Walle, Thomas Bäck, Jennifer L. Herek:
Evolution Strategies for Laser Pulse Compression. Artificial Evolution 2007: 219-230 - [c62]Ofer M. Shir, Michael Emmerich, Thomas Bäck:
Self-Adaptive Niching CMA-ES with Mahalanobis Metric. IEEE Congress on Evolutionary Computation 2007: 820-827 - [c61]Ofer M. Shir, Michael Emmerich, Thomas Bäck, Marc J. J. Vrakking:
The application of evolutionary multi-criteria optimization to dynamic molecular alignment. IEEE Congress on Evolutionary Computation 2007: 4108-4115 - [c60]Ofer M. Shir, Vered Raz, Roeland W. Dirks, Thomas Bäck:
Classification of Cell Fates with Support Vector Machine Learning. EvoBIO 2007: 258-269 - [c59]Rui Li, Jeroen Eggermont, Michael T. M. Emmerich, Ernst G. P. Bovenkamp, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Towards Dynamic Fitness Based Partitioning for IntraVascular UltraSound Image Analysis. EvoWorkshops 2007: 391-398 - [c58]Ofer M. Shir, Thomas Bäck:
Performance analysis of niching algorithms based on derandomized-ES variants. GECCO 2007: 705-712 - [c57]Ofer M. Shir, Thomas Bäck:
The second harmonic generation case-study as a gateway for es to quantum control problems. GECCO 2007: 713-721 - [c56]Ofer M. Shir, Thomas Bäck, Marc J. J. Vrakking:
On the scalability of evolution strategies in the optimization of dynamic molecular alignment. GECCO 2007: 2266 - [c55]Ofer M. Shir, Joost N. Kok, Thomas Bäck, Marc J. J. Vrakking:
Gaining Insights into Laser Pulse Shaping by Evolution Strategies. IWINAC (1) 2007: 467-477 - 2006
- [j18]Eric-Wubbo Lameijer, Joost N. Kok, Thomas Bäck, Adriaan P. IJzerman:
The Molecule Evoluator. An Interactive Evolutionary Algorithm for the Design of Drug-Like Molecules. J. Chem. Inf. Model. 46(2): 545-552 (2006) - [j17]Eric-Wubbo Lameijer, Joost N. Kok, Thomas Bäck, Adriaan P. IJzerman:
Mining a Chemical Database for Fragment Co-occurrence: Discovery of "Chemical Clichés". J. Chem. Inf. Model. 46(2): 553-562 (2006) - [j16]Jeroen Kazius, Siegfried Nijssen, Joost N. Kok, Thomas Bäck, Adriaan P. IJzerman:
Substructure Mining Using Elaborate Chemical Representation. J. Chem. Inf. Model. 46(2): 597-605 (2006) - [c54]Ofer M. Shir, Christian Siedschlag, Thomas Bäck, Marc J. J. Vrakking:
Evolutionary Algorithms in the Optimization of Dynamic Molecular Alignment. IEEE Congress on Evolutionary Computation 2006: 2912-2919 - [c53]Rui Li, Michael Emmerich, Ernst G. P. Bovenkamp, Jeroen Eggermont, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Mixed-Integer Evolution Strategies and Their Application to Intravascular Ultrasound Image Analysis. EvoWorkshops 2006: 415-426 - [c52]Ron Breukelaar, Michael Emmerich, Thomas Bäck:
On Interactive Evolution Strategies. EvoWorkshops 2006: 530-541 - [c51]Ofer M. Shir, Christian Siedschlag, Thomas Bäck, Marc J. J. Vrakking:
The complete-basis-functions parameterization in ES and its application to laser pulse shaping. GECCO 2006: 1769-1776 - [c50]Ofer M. Shir, Joost N. Kok, Thomas Bäck, Marc J. J. Vrakking:
Learning the Complete-Basis-Functions Parameterization for the Optimization of Dynamic Molecular Alignment by ES. IDEAL 2006: 410-418 - [c49]Rui Li, Michael T. M. Emmerich, Jeroen Eggermont, Ernst G. P. Bovenkamp, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Mixed-Integer NK Landscapes. PPSN 2006: 42-51 - [c48]Ofer M. Shir, Thomas Bäck:
Niche Radius Adaptation in the CMA-ES Niching Algorithm. PPSN 2006: 142-151 - 2005
- [j15]Eric-Wubbo Lameijer, Thomas Bäck, Joost N. Kok, Adriaan P. IJzerman:
Evolutionary Algorithms in Drug Design. Nat. Comput. 4(3): 177-243 (2005) - [c47]Ofer M. Shir, Christian Siedschlag, Thomas Bäck, Marc J. J. Vrakking:
Niching in Evolution Strategies and Its Application to Laser Pulse Shaping. Artificial Evolution 2005: 85-96 - [c46]Ofer M. Shir, Thomas Bäck:
Dynamic niching in evolution strategies with covariance matrix adaptation. Congress on Evolutionary Computation 2005: 2584-2591 - [c45]Ron Breukelaar, Thomas Bäck:
Using a genetic algorithm to evolve behavior in multi dimensional cellular automata: emergence of behavior. GECCO 2005: 107-114 - [c44]Ofer M. Shir, Thomas Bäck:
Niching in evolution strategies. GECCO 2005: 915-916 - [c43]Elena V. Samsonova, Thomas Bäck, Joost N. Kok, Adriaan P. IJzerman:
Reliable Hierarchical Clustering with the Self-organizing Map. IDA 2005: 385-396 - [c42]Thomas Bäck, Ron Breukelaar:
Using Genetic Algorithms to Evolve Behavior in Cellular Automata. UC 2005: 1-10 - 2004
- [j14]Jano I. van Hemert, Thomas Bäck:
Robust Parameter Settings for Variation Operators by Measuring the Resampling Ratio: A Study on Binary Constraint Satisfaction Problems. J. Heuristics 10(6): 629-640 (2004) - [j13]Thomas Bäck, Lars Willmes, Peter Krause:
Industrial Optimization by Evolution Strategies: A Bioinspired Optimization Algorithm. Informatica (Slovenia) 28(4): 337-344 (2004) - [j12]Thomas Bäck, Marc Schoenauer, Lars Willmes:
Preface. Nat. Comput. 3(1): 1-3 (2004) - [c41]Ron Breukelaar, Thomas Bäck:
Evolving Transition Rules for Multi Dimensional Cellular Automata. ACRI 2004: 182-191 - [c40]Thomas Bäck, Ron Breukelaar, Lars Willmes:
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm. UPP 2004: 161-172 - 2003
- [j11]Siegfried Nijssen, Thomas Bäck:
An analysis of the behavior of simplified evolutionary algorithms on trap functions. IEEE Trans. Evol. Comput. 7(1): 11-22 (2003) - [c39]Lars Willmes, Thomas Bäck, Yaochu Jin, Bernhard Sendhoff:
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization. IEEE Congress on Evolutionary Computation 2003: 663-670 - [c38]Lars Willmes, Thomas Bäck:
Multi-criteria Airfoil Design with Evolution Strategies. EMO 2003: 782-795 - [c37]Elena V. Samsonova, Thomas Bäck, Margot W. Beukers, Adriaan P. IJzerman, Joost N. Kok:
Combining and Comparing Cluster Methods in a Receptor Database. IDA 2003: 341-351 - 2002
- [j10]Thomas Bäck:
Evolutionary Computation: A Guided Tour. Bull. EATCS 77: 132-166 (2002) - [j9]Thomas Bäck:
Adaptive business intelligence based on evolution strategies: some application examples of self-adaptive software. Inf. Sci. 148(1-4): 113-121 (2002) - [c36]Boris Naujoks, Werner Haase, Jörg Ziegenhirt, Thomas Bäck:
Multi Objective Airfoil Design Using Single Parent Populations. GECCO 2002: 1156-1163 - [c35]Thomas Bäck:
Adaptive Business Intelligence Based on Evolution Strategies: Some Application Examples of Self-Adaptive Software. JCIS 2002: 2-6 - [c34]Thomas Bäck, Daniel Vermeulen, A. E. Eiben:
Effects of Tax and Evolution in an Artificial Society. JCIS 2002: 1151-1156 - [c33]Jano I. van Hemert, Thomas Bäck:
Measuring the Searched Space to Guide Efficiency: The Principle and Evidence on Constraint Satisfaction. PPSN 2002: 23-32 - [c32]Michael Emmerich, Alexios Giotis, Mutlu Özdemir, Thomas Bäck, Kyriakos C. Giannakoglou:
Metamodel-Assisted Evolution Strategies. PPSN 2002: 361-370 - [c31]Boris Naujoks, Lars Willmes, Thomas Bäck, Werner Haase:
Evaluating Multi-criteria Evolutionary Algorithms for Airfoil Optimisation. PPSN 2002: 841-850 - 2001
- [c30]Sandor Markon, Dirk V. Arnold, Thomas Bäck, Thomas Beielstein, Hans-Georg Beyer:
Thresholding-a selection operator for noisy ES. CEC 2001: 465-472 - [p1]Thomas Bäck, Jeannette M. de Graaf, Joost N. Kok, Walter A. Kosters:
Theory of Genetic Algorithms. Current Trends in Theoretical Computer Science 2001: 546-578 - 2000
- [c29]Ben Paechter, Thomas Bäck, Marc Schoenauer, Michèle Sebag, Ágoston E. Eiben, Juan Julián Merelo, Terence C. Fogarty:
A Distributed Resource Evolutionary Algorithm Machine (DREAM). CEC 2000: 951-958 - [c28]Thomas Bäck, A. E. Eiben, Nikolai A. L. van der Vaart:
An Empirical Study on GAs "Without Parameters". PPSN 2000: 315-324
1990 – 1999
- 1999
- [c27]Thomas Bäck, Joost N. Kok, Grzegorz Rozenberg:
Cross-fertilization between evolutionary computation and DNA-based computing. CEC 1999: 980-987 - [c26]Thomas Bäck, Ágoston E. Eiben:
Generalizations of intermediate recombination in evolution strategies. CEC 1999: 1566-1573 - [c25]Thomas Bäck, Martin Schütz, Raúl Héctor Gallard, Guillermo Leguizamón:
Improved Evolutionary Algorithms for Scheduling Problems. German-Argentinian Workshop on Information Technology 1999: 61-68 - 1998
- [j8]Thomas Bäck:
An Overview of Parameter Control Methods by Self-Adaption in Evolutionary Algorithms. Fundam. Informaticae 35(1-4): 51-66 (1998) - [j7]Dirk Wiesmann, Ulrich Hammel, Thomas Bäck:
Robust design of multilayer optical coatings by means of evolutionary algorithms. IEEE Trans. Evol. Comput. 2(4): 162-167 (1998) - [c24]Thomas Bäck, A. E. Eiben, Marco E. Vink:
A Superior Evolutionary Algorithm for 3-SAT. Evolutionary Programming 1998: 125-136 - [e3]A. E. Eiben, Thomas Bäck, Marc Schoenauer, Hans-Paul Schwefel:
Parallel Problem Solving from Nature - PPSN V, 5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings. Lecture Notes in Computer Science 1498, Springer 1998, ISBN 3-540-65078-4 [contents] - 1997
- [j6]Thomas Bäck:
Evolutionary computation: Toward a new philosophy of machine intelligence. Complex. 2(4): 28-30 (1997) - [j5]A. E. Eiben, Thomas Bäck:
Empirical Investigation of Multiparent Recombination Operators in Evolution Strategies. Evol. Comput. 5(3): 347-365 (1997) - [j4]Thomas Bäck, Ulrich Hammel, Hans-Paul Schwefel:
Evolutionary computation: comments on the history and current state. IEEE Trans. Evol. Comput. 1(1): 3-17 (1997) - [e2]Thomas Bäck:
Proceedings of the 7th International Conference on Genetic Algorithms, East Lansing, MI, USA, July 19-23, 1997. Morgan Kaufmann 1997 [contents] - 1996
- [b2]Thomas Bäck:
Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms. Oxford University Press 1996, ISBN 978-0-19-509971-3, pp. I-XII, 1-314 - [c23]Thomas Bäck, Hans-Paul Schwefel:
Evolutionary Computation: An Overview. International Conference on Evolutionary Computation 1996: 20-29 - [c22]Thomas Bäck, Jochen Heistermann, Cornelia Kappler, Michele Zamparelli:
Evolutionary Algorithms Support Refueling of Pressurized Water Reactors. International Conference on Evolutionary Computation 1996: 104-108 - [c21]Thomas Bäck, Martin Schütz:
Intelligent Mutation Rate Control in Canonical Genetic Algorithms. ISMIS 1996: 158-167 - [c20]Thomas Bäck, Holger Dörnemann, Ulrich Hammel, Pierre Frankhauser:
Modeling Urban Growth by Cellular Automata. PPSN 1996: 636-645 - [c19]Cornelia Kappler, Thomas Bäck, Jürgen Heistermann, A. Van der Velde, Michele Zamparelli:
Refueling of a Nuclear Power Plant: Comparison of a Naive and a Specialized Mutation Operator. PPSN 1996: 829-838 - [e1]Lawrence J. Fogel, Peter J. Angeline, Thomas Bäck:
Proceedings of the Fifth Annual Conference on Evolutionary Programming, EP 1996, San Diego, CA, USA, February 29 - March 2, 1996. MIT Press 1996, ISBN 0-262-06190-2 [contents] - 1995
- [c18]Thomas Bäck:
Evolution Strategies: An Alternative Evolutionary Algorithm. Artificial Evolution 1995: 3-20 - [c17]Thomas Bäck, Martin Schütz, Sami Khuri:
A Comparative Study of a Penalty Function, a Repair Heuristic and Stochastic Operators with the Set-Covering Problem. Artificial Evolution 1995: 320-332 - [c16]Thomas Bäck, Martin Schütz:
Evolution Strategies for Mixed-Integer Optimization of Optical Multilayer Systems. Evolutionary Programming 1995: 33-51 - [c15]Thomas Bäck:
Generalized Convergence Models for Tournament- and (mu, lambda)-Selection. ICGA 1995: 2-8 - 1994
- [b1]Thomas Bäck:
Evolutionary algorithms in theorie and practice. Technical University of Dortmund, Germany, 1994, pp. 1-284 - [j3]Thomas Bäck:
Book Review: Proceedings of the Fifth International Conference on Genetic Algorithms. Evol. Comput. 2(2): 181-191 (1994) - [c14]Sami Khuri, Thomas Bäck, Jörg Heitkötter:
An Evolutionary Approach to Combinatorial Optimization Problems. ACM Conference on Computer Science 1994: 66-73 - [c13]Thomas Bäck:
Order Statistics for Convergence Velocity Analysis of Simplified Evolutionary Algorithms. FOGA 1994: 91-102 - [c12]Thomas Bäck, Ulrich Hammel:
Evolution Strategies Applied to Perturbed Objective Functions. International Conference on Evolutionary Computation 1994: 40-45 - [c11]Thomas Bäck:
Selective Pressure in Evolutionary Algorithms: A Characterization of Selection Mechanisms. International Conference on Evolutionary Computation 1994: 57-62 - [c10]Thomas Bäck, Sami Khuri:
An Evolutionary Heuristic for the Maximum Independent Set Problem. International Conference on Evolutionary Computation 1994: 531-535 - [c9]Ulrich Hammel, Thomas Bäck:
Evolution Strategies on Noisy Functions: How to Improve Convergence Properties. PPSN 1994: 159-168 - [c8]Thomas Bäck:
Parallel Optimization of Evolutionary Algorithms. PPSN 1994: 418-427 - [c7]Sami Khuri, Thomas Bäck, Jörg Heitkötter:
The zero/one multiple knapsack problem and genetic algorithms. SAC 1994: 188-193 - 1993
- [j2]Thomas Bäck, Hans-Paul Schwefel:
An Overview of Evolutionary Algorithms for Parameter Optimization. Evol. Comput. 1(1): 1-23 (1993) - [c6]William M. Spears, Kenneth A. De Jong, Thomas Bäck, David B. Fogel, Hugo de Garis:
An Overview of Evolutionary Computation. ECML 1993: 442-459 - [c5]Thomas Bäck:
Optimal Mutation Rates in Genetic Search. ICGA 1993: 2-8 - 1992
- [j1]Hans-Paul Schwefel, Thomas Bäck:
Künstliche Evolution - eine intelligente Problemlösungsstrategie? Künstliche Intell. 6(2): 20-27 (1992) - [c4]Thomas Bäck:
The Interaction of Mutation Rate, Selection, and Self-Adaptation Within a Genetic Algorithm. PPSN 1992: 87-96 - 1991
- [c3]Thomas Bäck, Frank Hoffmeister, Hans-Paul Schwefel:
A Survey of Evolution Strategies. ICGA 1991: 2-9 - [c2]Thomas Bäck, Frank Hoffmeister:
Extended Selection Mechanisms in Genetic Algorithms. ICGA 1991: 92-99 - 1990
- [c1]Frank Hoffmeister, Thomas Bäck:
Genetic Algorithms and Evolution Strategies - Similarities and Differences. PPSN 1990: 455-469
Coauthor Index
[j68] [c287] [j65] [c280] [c276] [c269] [d23] [d22] [d21] [d20] [i105] [i103] [i84] [c266] [c253] [d18] [i75] [i70] [j45] [j44] [j43] [c244] [c243] [c240] [c238] [c233] [d15] [d14] [i69] [i67] [i65] [c223] [c217] [d12] [d11] [d10] [i52] [i51] [i39] [i34] [j36] [c203] [c202] [c200] [c185] [e6] [e5] [d3] [d2] [d1] [i25] [i24] [i21] [c175] [c166] [c163] [c162] [i18] [i17] [i13] [i12] [c144] [c141] [c135] [i10] [i9]
[c288] [i88] [j53] [c263] [c262] [i61] [j39] [i54] [j37] [c204] [c187] [c184] [c180] [e6] [e5] [i32] [i31] [i30] [i29] [i28] [i26] [j34] [j33] [j32] [c176] [c173] [c171] [c167] [c164] [i15] [c150] [c142] [j31] [j30] [j29] [c132] [c130] [c127] [c123] [i7] [j28] [j27] [c121] [c119] [c118] [c117] [c116] [c115] [j26] [j25] [c110] [c109] [c108] [c107] [c106] [c105] [c104] [c102] [c101] [i3] [c98] [c97] [i2] [j24] [c94] [c92] [i1] [c91] [c87] [j23] [c84] [c80] [c79] [c77] [c76] [c75] [c74] [j21] [c72] [c71] [c66] [c64] [c62] [c61] [c59] [c53] [c52] [c49] [c32]
Roman Kalkreuth
aka: Roman T. Kalkreuth
aka: Roman T. Kalkreuth
[j70] [c286] [i118] [i114] [i113] [i111] [j66] [c281] [c276] [c272] [c271] [c270] [c267] [e14] [e13] [e12] [e11] [d23] [i110] [i108] [i107] [i106] [i105] [i102] [i97] [i95] [i91] [i90] [i86] [i85] [j61] [j60] [j55] [c261] [c259] [c255] [c254] [c251] [c250] [c249] [c248] [d19] [i80] [i78] [i77] [i76] [i73] [j52] [c236] [c235] [c231] [i57] [i55] [j40] [c226] [c219] [c216] [c210] [i41] [i40] [i38] [c205] [c188] [i27]
Niki van Stein
aka: Bas van Stein
aka: Bas van Stein
[j69] [c286] [i116] [i114] [i113] [i111] [j63] [j62] [c283] [c281] [c279] [c275] [c274] [c268] [i110] [i109] [i108] [i101] [i99] [i96] [i94] [i93] [i90] [i89] [i85] [j59] [j58] [j55] [c259] [c257] [c252] [c250] [d19] [i81] [i77] [i76] [i72] [j51] [j49] [j47] [j46] [c241] [c239] [c231] [e10] [i68] [i59] [i55] [c230] [c229] [c228] [c225] [c212] [c209] [j37] [c204] [c194] [c183] [c181] [c180] [i29] [i20] [c160] [c156] [c154] [c153] [c137] [c136] [i8] [c129] [c127] [c125] [c123] [i7] [c122] [c118] [c114] [c112] [i4] [c102]
Diederick Vermetten
aka: Diederick L. Vermetten
aka: Diederick L. Vermetten
[j68] [c287] [i121] [i119] [i118] [j65] [c280] [c279] [c277] [c276] [c272] [c271] [c270] [c269] [c267] [d23] [d22] [d21] [d20] [i110] [i106] [i105] [i103] [i102] [i91] [i89] [i84] [j55] [c266] [c265] [c258] [c256] [c255] [c254] [c253] [c250] [d19] [d18] [i83] [i80] [i78] [i77] [i75] [i70] [j43] [c244] [c240] [c238] [c233] [d15] [d14] [i69] [i67] [i65] [c219] [c217] [d12] [i51] [i41] [i34] [c203] [c202] [i24] [i21] [c166] [i17] [i13]
[i121] [i119] [i118] [i117] [i115] [j65] [c284] [c277] [c276] [d23] [i105] [i104] [i87] [j55] [j54] [c265] [c253] [c247] [c246] [i83] [i79] [i74] [i71] [j44] [j43] [c244] [c243] [c240] [c238] [c232] [d15] [i67] [i65] [j42] [j41] [c226] [c224] [c222] [c219] [c218] [c217] [d12] [d10] [i51] [i45] [i41] [i39] [i34] [j37] [j36] [c208] [c205] [c203] [c202] [c200] [c199] [c193] [c192] [c188] [c185] [c182] [c181] [c179] [c178] [e6] [e5] [d9] [d4] [d3] [d2] [d1] [i33] [i25] [i24] [i22] [i21] [i20] [j34] [c177] [c174] [c171] [c163] [c162] [c160] [c159] [c155] [c152] [i13] [i12] [c150] [c145] [c144] [c140] [c137] [i10] [i9] [i8] [c130] [c129] [c127] [c124] [c123] [i7] [c121] [c118] [c115] [c111] [i5] [c104] [c102] [c97]
[j68] [j65] [c273] [c272] [d21] [d20] [i106] [i92] [j55] [c266] [c265] [c258] [c256] [c255] [c253] [d18] [i83] [i82] [i78] [i75] [i70] [j44] [j43] [c244] [c243] [c238] [c233] [d14] [i69] [c223] [d12] [d11] [d10] [i52] [i39] [i34] [j36] [c185] [d3] [d2] [d1] [i25] [i21] [c175] [c162] [i18] [i12] [c144] [i10] [i9]
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