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Dirk Thierens
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2020 – today
- 2024
- [c83]Dirk Thierens, Peter A. N. Bosman:
Model-Based Evolutionary Algorithms. GECCO Companion 2024: 1096-1126 - [c82]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching. GECCO Companion 2024: 1914-1923 - [i8]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Stitching for Neuroevolution: Recombining Deep Neural Networks without Breaking Them. CoRR abs/2403.14224 (2024) - [i7]Sjoerd de Vries, Dirk Thierens:
Learning with Confidence: Training Better Classifiers from Soft Labels. CoRR abs/2409.16071 (2024) - 2023
- [c81]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
The Impact of Asynchrony on Parallel Model-Based EAs. GECCO 2023: 910-918 - [c80]Dirk Thierens, Peter A. N. Bosman:
Model-Based Evolutionary Algorithms. GECCO Companion 2023: 1099-1128 - [i6]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
The Impact of Asynchrony on Parallel Model-Based EAs. CoRR abs/2303.15543 (2023) - [i5]Sjoerd de Vries, Dirk Thierens:
Generating the Ground Truth: Synthetic Data for Label Noise Research. CoRR abs/2309.04318 (2023) - 2022
- [j13]Sjoerd de Vries, Thijs ten Doesschate, Joan E. E. Totté, Judith W. Heutz, Yvette G. T. Loeffen, Jan Jelrik Oosterheert, Dirk Thierens, Edwin Boel:
A semi-supervised decision support system to facilitate antibiotic stewardship for urinary tract infections. Comput. Biol. Medicine 146: 105621 (2022) - [c79]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Solving multi-structured problems by introducing linkage kernels into GOMEA. GECCO 2022: 703-711 - [c78]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2022 tutorial. GECCO Companion 2022: 1141-1170 - [d1]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Solving multi-structured problems by introducing linkage kernels into GOMEA - Source Code. Zenodo, 2022 - [i4]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Solving Multi-Structured Problems by Introducing Linkage Kernels into GOMEA. CoRR abs/2203.05970 (2022) - 2021
- [j12]Sjoerd de Vries, Dirk Thierens:
A reliable ensemble based approach to semi-supervised learning. Knowl. Based Syst. 215: 106738 (2021) - [c77]Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman:
Optimization of multi-objective mixed-integer problems with a model-based evolutionary algorithm in a black-box setting. GECCO Companion 2021: 227-228 - [c76]Dirk Thierens, Tobias van Driessel:
A benchmark generator of tree decomposition Mk landscapes. GECCO Companion 2021: 229-230 - [c75]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. GECCO Companion 2021: 558-587 - [c74]Tobias van Driessel, Dirk Thierens:
Benchmark generator for TD Mk landscapes. GECCO Companion 2021: 1227-1233 - [c73]Michal Witold Przewozniczek, Marcin M. Komarnicki, Peter A. N. Bosman, Dirk Thierens, Bartosz Frej, Ngoc Hoang Luong:
Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. GECCO Companion 2021: 1442-1450 - [p4]Stefanus C. Maree, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Two-Phase Real-Valued Multimodal Optimization with the Hill-Valley Evolutionary Algorithm. Metaheuristics for Finding Multiple Solutions 2021: 165-189 - [i3]Arkadiy Dushatskiy, Marco Virgolin, Anton Bouter, Dirk Thierens, Peter A. N. Bosman:
Parameterless Gene-pool Optimal Mixing Evolutionary Algorithms. CoRR abs/2109.05259 (2021) - 2020
- [c72]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2020 tutorial. GECCO Companion 2020: 590-619
2010 – 2019
- 2019
- [c71]Rogier Hans Wuijts, Dirk Thierens:
Investigation of the traveling thief problem. GECCO 2019: 329-337 - [c70]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. GECCO (Companion) 2019: 806-836 - 2018
- [j11]Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman:
GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems. Evol. Comput. 26(1) (2018) - [c69]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2018 tutorial. GECCO (Companion) 2018: 553-583 - [c68]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Real-valued evolutionary multi-modal optimization driven by hill-valley clustering. GECCO 2018: 857-864 - [c67]Kalia Orphanou, Dirk Thierens, Peter A. N. Bosman:
Learning bayesian network structures with GOMEA. GECCO 2018: 1007-1014 - [c66]G. H. Aalvanger, Ngoc Hoang Luong, Peter A. N. Bosman, Dirk Thierens:
Heuristics in Permutation GOMEA for Solving the Permutation Flowshop Scheduling Problem. PPSN (1) 2018: 146-157 - [i2]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Benchmarking the Hill-Valley Evolutionary Algorithm for the GECCO 2018 Competition on Niching Methods Multimodal Optimization. CoRR abs/1807.00188 (2018) - [i1]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Real-Valued Evolutionary Multi-Modal Optimization driven by Hill-Valley Clustering. CoRR abs/1810.07085 (2018) - 2017
- [c65]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2017 tutorial. GECCO (Companion) 2017: 545-575 - [c64]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Niching an estimation-of-distribution algorithm by hierarchical Gaussian mixture learning. GECCO 2017: 713-720 - [c63]Krzysztof L. Sadowski, Marjolein C. van der Meer, Ngoc Hoang Luong, Tanja Alderliesten, Dirk Thierens, Rob van der Laarse, Yury Niatsetski, Arjan Bel, Peter A. N. Bosman:
Exploring trade-offs between target coverage, healthy tissue sparing, and the placement of catheters in HDR brachytherapy for prostate cancer using a novel multi-objective model-based mixed-integer evolutionary algorithm. GECCO 2017: 1224-1231 - 2016
- [c62]Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens:
Learning and exploiting mixed variable dependencies with a model-based EA. CEC 2016: 4382-4389 - [c61]Dirk Thierens, Peter A. N. Bosman:
Model-Based Evolutionary Algorithms. GECCO (Companion) 2016: 385-412 - [c60]Peter A. N. Bosman, Ngoc Hoang Luong, Dirk Thierens:
Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms. GECCO 2016: 637-644 - [c59]Willem den Besten, Dirk Thierens, Peter A. N. Bosman:
The Multiple Insertion Pyramid: A Fast Parameter-Less Population Scheme. PPSN 2016: 48-58 - 2015
- [c58]Dirk Thierens, Peter A. N. Bosman:
Model-Based Evolutionary Algorithms. GECCO (Companion) 2015: 93-120 - [c57]Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens:
A Clustering-Based Model-Building EA for Optimization Problems with Binary and Real-Valued Variables. GECCO 2015: 911-918 - [c56]Roy de Bokx, Dirk Thierens, Peter A. N. Bosman:
In Search of Optimal Linkage Trees. GECCO (Companion) 2015: 1375-1376 - 2014
- [c55]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. GECCO (Companion) 2014: 431-458 - [c54]Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman:
Combining Model-Based EAs for Mixed-Integer Problems. PPSN 2014: 342-351 - 2013
- [j10]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
Benchmarking Parameter-Free AMaLGaM on Functions With and Without Noise. Evol. Comput. 21(3): 445-469 (2013) - [c53]Peter A. N. Bosman, Dirk Thierens:
More concise and robust linkage learning by filtering and combining linkage hierarchies. GECCO 2013: 359-366 - [c52]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. GECCO (Companion) 2013: 377-404 - [c51]Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens:
On the usefulness of linkage processing for solving MAX-SAT. GECCO 2013: 853-860 - [c50]Dirk Thierens, Peter A. N. Bosman:
Hierarchical problem solving with the linkage tree genetic algorithm. GECCO 2013: 877-884 - 2012
- [j9]Madalina M. Drugan, Dirk Thierens:
Stochastic Pareto local search: Pareto neighbourhood exploration and perturbation strategies. J. Heuristics 18(5): 727-766 (2012) - [c49]Dirk Thierens, Peter A. N. Bosman:
Predetermined versus learned linkage models. GECCO 2012: 289-296 - [c48]Peter A. N. Bosman, Dirk Thierens:
Linkage neighbors, optimal mixing and forced improvements in genetic algorithms. GECCO 2012: 585-592 - [c47]Dirk Thierens, Peter A. N. Bosman:
Learning the Neighborhood with the Linkage Tree Genetic Algorithm. LION 2012: 491-496 - [c46]Peter A. N. Bosman, Dirk Thierens:
On Measures to Build Linkage Trees in LTGA. PPSN (1) 2012: 276-285 - [c45]Dirk Thierens, Peter A. N. Bosman:
Evolvability Analysis of the Linkage Tree Genetic Algorithm. PPSN (1) 2012: 286-295 - 2011
- [c44]Dirk Thierens, Peter A. N. Bosman:
Optimal mixing evolutionary algorithms. GECCO 2011: 617-624 - [c43]Peter A. N. Bosman, Dirk Thierens:
The roles of local search, model building and optimal mixing in evolutionary algorithms from a bbo perspective. GECCO (Companion) 2011: 663-670 - [c42]Martin Pelikan, Mark Hauschild, Dirk Thierens:
Pairwise and problem-specific distance metrics in the linkage tree genetic algorithm. GECCO 2011: 1005-1012 - [c41]Madalina M. Drugan, Dirk Thierens:
Generalized adaptive pursuit algorithm for genetic pareto local search algorithms. GECCO 2011: 1963-1970 - 2010
- [j8]Madalina M. Drugan, Dirk Thierens:
Geometrical Recombination Operators for Real-Coded Evolutionary MCMCs. Evol. Comput. 18(2): 157-198 (2010) - [j7]Madalina M. Drugan, Dirk Thierens:
Recombination operators and selection strategies for evolutionary Markov Chain Monte Carlo algorithms. Evol. Intell. 3(2): 79-101 (2010) - [c40]Dirk Thierens:
Linkage tree genetic algorithm: first results. GECCO (Companion) 2010: 1953-1958 - [c39]Dirk Thierens:
The Linkage Tree Genetic Algorithm. PPSN (1) 2010: 264-273 - [c38]Madalina M. Drugan, Dirk Thierens:
Path-Guided Mutation for Stochastic Pareto Local Search Algorithms. PPSN (1) 2010: 485-495
2000 – 2009
- 2009
- [c37]Dirk Thierens:
On benchmark properties for adaptive operator selection. GECCO (Companion) 2009: 2217-2218 - [c36]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
AMaLGaM IDEAs in noiseless black-box optimization benchmarking. GECCO (Companion) 2009: 2247-2254 - [c35]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
AMaLGaM IDEAs in noisy black-box optimization benchmarking. GECCO (Companion) 2009: 2351-2358 - [c34]Dirk Thierens:
Adaptive Operator Selection for Iterated Local Search. SLS 2009: 140-144 - 2008
- [c33]Dirk Thierens:
A bivariate probabilistic model-building genetic algorithm for graph bipartitioning. GECCO (Companion) 2008: 2089-2092 - [c32]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
Enhancing the Performance of Maximum-Likelihood Gaussian EDAs Using Anticipated Mean Shift. PPSN 2008: 133-143 - 2007
- [c31]Peter A. N. Bosman, Dirk Thierens:
Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. GECCO 2007: 500-507 - [p3]Dirk Thierens:
Adaptive Strategies for Operator Allocation. Parameter Setting in Evolutionary Algorithms 2007: 77-90 - [e3]Dirk Thierens:
Genetic and Evolutionary Computation Conference, GECCO 2007, Proceedings, London, England, UK, July 7-11, 2007, Companion Material. ACM 2007, ISBN 978-1-59593-698-1 [contents] - 2006
- [c30]Dirk Thierens:
Exploration and Exploitation Bias of Crossover and Path Relinking for Permutation Problems. PPSN 2006: 1028-1037 - [p2]Peter A. N. Bosman, Dirk Thierens:
Multi-objective Optimization with the Naive 𝕄 ID 𝔼 A. Towards a New Evolutionary Computation 2006: 123-157 - [p1]Peter A. N. Bosman, Dirk Thierens:
Numerical Optimization with Real-Valued Estimation-of-Distribution Algorithms. Scalable Optimization via Probabilistic Modeling 2006: 91-120 - 2005
- [c29]Edwin D. de Jong, Richard A. Watson, Dirk Thierens:
On the Complexity of Hierarchical Problem Solving. BNAIC 2005: 339-340 - [c28]Dirk Thierens:
An Adaptive Pursuit Strategy for Allocating Operator Probabilities. BNAIC 2005: 385-386 - [c27]Madalina M. Drugan, Dirk Thierens:
Recombinative EMCMC algorithms. Congress on Evolutionary Computation 2005: 2024-2031 - [c26]Peter A. N. Bosman, Dirk Thierens:
The Naive MIDEA: A Baseline Multi-objective EA. EMO 2005: 428-442 - [c25]Edwin D. de Jong, Richard A. Watson, Dirk Thierens:
A generator for hierarchical problems. GECCO Workshops 2005: 321-326 - [c24]Edwin D. de Jong, Richard A. Watson, Dirk Thierens:
On the complexity of hierarchical problem solving. GECCO 2005: 1201-1208 - [c23]Dirk Thierens:
An adaptive pursuit strategy for allocating operator probabilities. GECCO 2005: 1539-1546 - 2004
- [j6]Steven van Dijk, Dirk Thierens, Mark de Berg:
On the Design and Analysis of Competent Selecto-recombinative GAs. Evol. Comput. 12(2): 243-267 (2004) - [c22]Dirk Thierens:
Population-Based Iterated Local Search: Restricting Neighborhood Search by Crossover. GECCO (2) 2004: 234-245 - [c21]Edwin D. de Jong, Dirk Thierens:
Exploiting Modularity, Hierarchy, and Repetition in Variable-Length Problems. GECCO (1) 2004: 1030-1041 - [c20]Steven van Dijk, Dirk Thierens:
On the Use of a Non-redundant Encoding for Learning Bayesian Networks from Data with a GA. PPSN 2004: 141-150 - [c19]Edwin D. de Jong, Dirk Thierens, Richard A. Watson:
Hierarchical Genetic Algorithms. PPSN 2004: 232-241 - [e2]Kalyanmoy Deb, Riccardo Poli, Wolfgang Banzhaf, Hans-Georg Beyer, Edmund K. Burke, Paul J. Darwen, Dipankar Dasgupta, Dario Floreano, James A. Foster, Mark Harman, Owen Holland, Pier Luca Lanzi, Lee Spector, Andrea Tettamanzi, Dirk Thierens, Andrew M. Tyrrell:
Genetic and Evolutionary Computation - GECCO 2004, Genetic and Evolutionary Computation Conference, Seattle, WA, USA, June 26-30, 2004, Proceedings, Part I. Lecture Notes in Computer Science 3102, Springer 2004, ISBN 3-540-22344-4 [contents] - [e1]Kalyanmoy Deb, Riccardo Poli, Wolfgang Banzhaf, Hans-Georg Beyer, Edmund K. Burke, Paul J. Darwen, Dipankar Dasgupta, Dario Floreano, James A. Foster, Mark Harman, Owen Holland, Pier Luca Lanzi, Lee Spector, Andrea Tettamanzi, Dirk Thierens, Andrew M. Tyrrell:
Genetic and Evolutionary Computation - GECCO 2004, Genetic and Evolutionary Computation Conference, Seattle, WA, USA, June 26-30, 2004, Proceedings, Part II. Lecture Notes in Computer Science 3103, Springer 2004, ISBN 3-540-22343-6 [contents] - 2003
- [j5]Peter A. N. Bosman, Dirk Thierens:
The balance between proximity and diversity in multiobjective evolutionary algorithms. IEEE Trans. Evol. Comput. 7(2): 174-188 (2003) - [c18]Madalina M. Drugan, Dirk Thierens:
Evolutionary Markov Chain Monte Carlo. Artificial Evolution 2003: 63-76 - [c17]Dirk Thierens:
Convergence Time Analysis for the Multi-objective Counting Ones Problem. EMO 2003: 355-364 - [c16]Steven van Dijk, Dirk Thierens, Linda C. van der Gaag:
Building a GA from Design Principles for Learning Bayesian Networks. GECCO 2003: 886-897 - [c15]Steven van Dijk, Linda C. van der Gaag, Dirk Thierens:
A Skeleton-Based Approach to Learning Bayesian Networks from Data. PKDD 2003: 132-143 - 2002
- [j4]Steven van Dijk, Dirk Thierens, Mark de Berg:
Using Genetic Algorithms for Solving Hard Problems in GIS. GeoInformatica 6(4): 381-413 (2002) - [j3]Peter A. N. Bosman, Dirk Thierens:
Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms. Int. J. Approx. Reason. 31(3): 259-289 (2002) - [c14]Dirk Thierens:
Adaptive mutation rate control schemes in genetic algorithms. IEEE Congress on Evolutionary Computation 2002: 980-985 - [c13]Peter A. N. Bosman, Dirk Thierens:
Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations. PPSN 2002: 331-340 - 2001
- [j2]Hillol Kargupta, Dirk Thierens:
Computation in Gene Expression. Complex Syst. 13(1) (2001) - 2000
- [c12]Steven van Dijk, Dirk Thierens, Mark de Berg:
Scalability and Efficiency of Genetic Algorithms for Geometrical Applications. PPSN 2000: 683-692 - [c11]Peter A. N. Bosman, Dirk Thierens:
Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA. PPSN 2000: 767-776
1990 – 1999
- 1999
- [j1]Dirk Thierens:
Scalability Problems of Simple Genetic Algorithms. Evol. Comput. 7(4): 331-352 (1999) - [c10]Martijn Neef, Dirk Thierens, Henryk F. R. Arciszewski:
A case study of a multiobjective recombinative genetic algorithm with coevolutionary sharing. CEC 1999: 796-806 - [c9]Peter A. N. Bosman, Dirk Thierens:
Linkage Information Processing In Distribution Estimation Algorithms. GECCO 1999: 60-67 - [c8]Steven van Dijk, Dirk Thierens, Mark de Berg:
On The Design of Genetic Algorithms for Geographical Applications. GECCO 1999: 188-195 - 1997
- [c7]Dirk Thierens:
Selection Schemes, Elitist Recombination, and Selection Intensity. ICGA 1997: 152-159 - 1996
- [c6]Dirk Thierens:
Non-Redundant Genetic Coding of Neural Networks. International Conference on Evolutionary Computation 1996: 571-575 - [c5]Dirk Thierens:
Dimensional Analysis of Allele-Wise Mixing Revisited. PPSN 1996: 255-265 - 1994
- [c4]Dirk Thierens, David E. Goldberg:
Elitist Recombination: An Integrated Selection Recombination GA. International Conference on Evolutionary Computation 1994: 508-512 - [c3]Dirk Thierens, David E. Goldberg:
Convergence Models of Genetic Algorithm Selection Schemes. PPSN 1994: 119-129 - 1993
- [c2]Dirk Thierens, David E. Goldberg:
Mixing in Genetic Algorithms. ICGA 1993: 38-47 - 1990
- [c1]Dirk Thierens, Leo Vercauteren:
A Topology Exploiting Genetic Algorithm to Control Dynamic Systems. PPSN 1990: 104-108
Coauthor Index
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