Linkage Information Processing In Distribution Estimation Algorithms. - Peter A. N. Bosman; Dirk Thierens (GECCO, 1999)

Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA. - Peter A. N. Bosman; Dirk Thierens (PPSN, 2000)

Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations. - Peter A. N. Bosman; Dirk Thierens (PPSN, 2002)

Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms. - Peter A. N. Bosman; Dirk Thierens (Int. J. Approx. Reason., 2002)

The balance between proximity and diversity in multiobjective evolutionary algorithms. - Peter A. N. Bosman; Dirk Thierens (IEEE Trans. Evol. Comput., 2003)

Learning Probabilistic Tree Grammars for Genetic Programming. - Peter A. N. Bosman; Edwin D. de Jong (PPSN, 2004)

The Naive MIDEA: A Baseline Multi-objective EA. - Peter A. N. Bosman; Dirk Thierens (EMO, 2005)

Learning, anticipation and time-deception in evolutionary online dynamic optimization. - Peter A. N. Bosman (GECCO Workshops, 2005)

Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions. - Peter A. N. Bosman; Tanja Alderliesten (GECCO Workshops, 2005)

Exploiting gradient information in numerical multi–objective evolutionary optimization. - Peter A. N. Bosman; Edwin D. de Jong (GECCO, 2005)

Multi-objective Optimization with the Naive 𝕄 ID 𝔼 A. - Peter A. N. Bosman; Dirk Thierens (Towards a New Evolutionary Computation, 2006)

Combining gradient techniques for numerical multi-objective evolutionary optimization. - Peter A. N. Bosman; Edwin D. de Jong (GECCO, 2006)

The correlation-triggered adaptive variance scaling IDEA. - Jörn Grahl; Peter A. N. Bosman; Franz Rothlauf (GECCO, 2006)

Computationally Intelligent Online Dynamic Vehicle Routing by Explicit Load Prediction in an Evolutionary Algorithm. - Peter A. N. Bosman; Han La Poutré (PPSN, 2006)

Numerical Optimization with Real-Valued Estimation-of-Distribution Algorithms. - Peter A. N. Bosman; Dirk Thierens (Scalable Optimization via Probabilistic Modeling, 2006)

Inventory management and the impact of anticipation in evolutionary stochastic online dynamic optimization. - Peter A. N. Bosman; Han La Poutré (IEEE Congress on Evolutionary Computation, 2007)

SDR: a better trigger for adaptive variance scaling in normal EDAs. - Peter A. N. Bosman; Jörn Grahl; Franz Rothlauf (GECCO, 2007)

Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case. - Peter A. N. Bosman; Han La Poutré (GECCO, 2007)

Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. - Peter A. N. Bosman; Dirk Thierens (GECCO, 2007)

Convergence phases, variance trajectories, and runtime analysis of continuous EDAs. - Jörn Grahl; Peter A. N. Bosman; Stefan Minner (GECCO, 2007)

Towards a Real-Time Minimally-Invasive Vascular Intervention Simulation System. - Tanja Alderliesten; Peter A. N. Bosman; Wiro J. Niessen (IEEE Trans. Medical Imaging, 2007)

Learning and Anticipation in Online Dynamic Optimization. - Peter A. N. Bosman (Evolutionary Computation in Dynamic and Uncertain Environments, 2007)

Agent-based patient admission scheduling in hospitals. - Anke K. Hutzschenreuter; Peter A. N. Bosman; Ilona Blonk-Altena; Jan van Aarle; Han La Poutré (AAMAS (Industry Track), 2008)

Learning Structure Illuminates Black Boxes - An Introduction to Estimation of Distribution Algorithms. - Jörn Grahl; Stefan Minner; Peter A. N. Bosman (Advances in Metaheuristics for Hard Optimization, 2008)

Enhancing the Performance of Maximum-Likelihood Gaussian EDAs Using Anticipated Mean Shift. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (PPSN, 2008)

Matching inductive search bias and problem structure in continuous Estimation-of-Distribution Algorithms. - Peter A. N. Bosman; Jörn Grahl (Eur. J. Oper. Res., 2008)

Optimization of Online Patient Scheduling with Urgencies and Preferences. - Ivan B. Vermeulen; Sander M. Bohté; Peter A. N. Bosman; Sylvia G. Elkhuizen; Piet J. M. Bakker; Johannes A. La Poutré (AIME, 2009)

Evolutionary Multiobjective Optimization for Dynamic Hospital Resource Management. - Anke K. Hutzschenreuter; Peter A. N. Bosman; Han La Poutré (EMO, 2009)

On empirical memory design, faster selection of bayesian factorizations and parameter-free gaussian EDAs. - Peter A. N. Bosman (GECCO, 2009)

AMaLGaM IDEAs in noiseless black-box optimization benchmarking. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (GECCO (Companion), 2009)

AMaLGaM IDEAs in noisy black-box optimization benchmarking. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (GECCO (Companion), 2009)

The anticipated mean shift and cluster registration in mixture-based EDAs for multi-objective optimization. - Peter A. N. Bosman (GECCO, 2010)

Enhanced hospital resource management using anticipatory policies in online dynamic multi-objective optimization. - Anke K. Hutzschenreuter; Peter A. N. Bosman; Han La Poutré (GECCO, 2010)

A Computational Approach to Patient Flow Logistics in Hospitals. - Anke K. Hutzschenreuter; Peter A. N. Bosman; Han La Poutré (ERCIM News, 2010)

The roles of local search, model building and optimal mixing in evolutionary algorithms from a bbo perspective. - Peter A. N. Bosman; Dirk Thierens (GECCO (Companion), 2011)

Optimal mixing evolutionary algorithms. - Dirk Thierens; Peter A. N. Bosman (GECCO, 2011)

Adaptive Strategies for Dynamic Pricing Agents. - Sara Ramezani; Peter A. N. Bosman; Han La Poutré (IAT, 2011)

Incremental gaussian model-building in multi-objective EDAs with an application to deformable image registration. - Peter A. N. Bosman; Tanja Alderliesten (GECCO, 2012)

Linkage neighbors, optimal mixing and forced improvements in genetic algorithms. - Peter A. N. Bosman; Dirk Thierens (GECCO, 2012)

Predetermined versus learned linkage models. - Dirk Thierens; Peter A. N. Bosman (GECCO, 2012)

Learning the Neighborhood with the Linkage Tree Genetic Algorithm. - Dirk Thierens; Peter A. N. Bosman (LION, 2012)

Multi-objective optimization for deformable image registration: proof of concept. - Tanja Alderliesten; Jan-Jakob Sonke; Peter A. N. Bosman (Image Processing, 2012)

On Measures to Build Linkage Trees in LTGA. - Peter A. N. Bosman; Dirk Thierens (PPSN (1), 2012)

Elitist Archiving for Multi-Objective Evolutionary Algorithms: To Adapt or Not to Adapt. - Hoang N. Luong; Peter A. N. Bosman (PPSN (2), 2012)

Evolvability Analysis of the Linkage Tree Genetic Algorithm. - Dirk Thierens; Peter A. N. Bosman (PPSN (1), 2012)

On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization. - Peter A. N. Bosman (IEEE Trans. Evol. Comput., 2012)

Medium-Voltage Distribution Network Expansion Planning with Gene-pool Optimal Mixing Evolutionary Algorithms. - Hoang N. Luong; Marinus O. W. Grond; Peter A. N. Bosman; Han La Poutré (Artificial Evolution, 2013)

More concise and robust linkage learning by filtering and combining linkage hierarchies. - Peter A. N. Bosman; Dirk Thierens (GECCO, 2013)

Solving satisfiability in fuzzy logics by mixing CMA-ES. - Tim Brys; Madalina M. Drugan; Peter A. N. Bosman; Martine De Cock; Ann Nowé (GECCO, 2013)

On the usefulness of linkage processing for solving MAX-SAT. - Krzysztof L. Sadowski; Peter A. N. Bosman; Dirk Thierens (GECCO, 2013)

Hierarchical problem solving with the linkage tree genetic algorithm. - Dirk Thierens; Peter A. N. Bosman (GECCO, 2013)

Local search and restart strategies for satisfiability solving in fuzzy logics. - Tim Brys; Madalina M. Drugan; Peter A. N. Bosman; Martine De Cock; Ann Nowé (GEFS, 2013)

Deformable image registration by multi-objective optimization using a dual-dynamic transformation model to account for large anatomical differences. - Tanja Alderliesten; Jan-Jakob Sonke; Peter A. N. Bosman (Image Processing, 2013)

Benchmarking Parameter-Free AMaLGaM on Functions With and Without Noise. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (Evol. Comput., 2013)

Market Garden: A Scalable Research Environment for Heterogeneous Electricity Markets. - Felix Claessen; Nicolas Höning; Bart Liefers; Han La Poutré; Peter A. N. Bosman (ERCIM News, 2013)

Efficiency enhancements for evolutionary capacity planning in distribution grids. - Ngoc Hoang Luong; Marinus O. W. Grond; Han La Poutré; Peter A. N. Bosman (GECCO (Companion), 2014)

Multi-objective gene-pool optimal mixing evolutionary algorithms. - Ngoc Hoang Luong; Han La Poutré; Peter A. N. Bosman (GECCO, 2014)

A novel population-based multi-objective CMA-ES and the impact of different constraint handling techniques. - Sílvio Miguel Fragoso Rodrigues; Pavol Bauer; Peter A. N. Bosman (GECCO, 2014)

Model-based evolutionary algorithms. - Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2014)

A multi-resolution strategy for a multi-objective deformable image registration framework that accommodates large anatomical differences. - Tanja Alderliesten; Peter A. N. Bosman; Jan-Jakob Sonke; Arjan Bel (Image Processing, 2014)

Market Garden: A Simulation Environment for Research and User Experience in Smart Grids. - Bart Liefers; Felix Claessen; Eric J. Pauwels; Peter A. N. Bosman; Han La Poutré (PAAMS, 2014)

Combining Model-Based EAs for Mixed-Integer Problems. - Krzysztof L. Sadowski; Dirk Thierens; Peter A. N. Bosman (PPSN, 2014)

Practice-oriented optimization of distribution network planning using metaheuristic algorithms. - Marinus O. W. Grond; Ngoc Hoang Luong; Johan Morren; Peter A. N. Bosman; Han Slootweg; Han La Poutré (PSCC, 2014)

In Search of Optimal Linkage Trees. - Roy de Bokx; Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2015)

Diversifying Multi-Objective Gradient Techniques and their Role in Hybrid Multi-Objective Evolutionary Algorithms for Deformable Medical Image Registration. - Kleopatra Pirpinia; Tanja Alderliesten; Jan-Jakob Sonke; Marcel van Herk; Peter A. N. Bosman (GECCO, 2015)

A Clustering-Based Model-Building EA for Optimization Problems with Binary and Real-Valued Variables. - Krzysztof L. Sadowski; Peter A. N. Bosman; Dirk Thierens (GECCO, 2015)

Getting the most out of additional guidance information in deformable image registration by leveraging multi-objective optimization. - Tanja Alderliesten; Peter A. N. Bosman; Arjan Bel (Image Processing, 2015)

On the usefulness of gradient information in multi-objective deformable image registration using a B-spline-based dual-dynamic transformation model: comparison of three optimization algorithms. - Kleopatra Pirpinia; Peter A. N. Bosman; Jan-Jakob Sonke; Marcel van Herk; Tanja Alderliesten (Image Processing, 2015)

Learning and exploiting mixed variable dependencies with a model-based EA. - Krzysztof L. Sadowski; Peter A. N. Bosman; Dirk Thierens (CEC, 2016)

Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms. - Peter A. N. Bosman; Ngoc Hoang Luong; Dirk Thierens (GECCO, 2016)

GECCO'16 Model-Based Evolutionary Algorithms (MBEA) Workshop Chairs' Welcome. - Peter A. N. Bosman; John A. W. McCall (GECCO (Companion), 2016)

Smart grid initialization reduces the computational complexity of multi-objective image registration based on a dual-dynamic transformation model to account for large anatomical differences. - Peter A. N. Bosman; Tanja Alderliesten (Image Processing, 2016)

A first step toward uncovering the truth about weight tuning in deformable image registration. - Kleopatra Pirpinia; Peter A. N. Bosman; Jan-Jakob Sonke; Marcel van Herk; Tanja Alderliesten (Image Processing, 2016)

The Multiple Insertion Pyramid: A Fast Parameter-Less Population Scheme. - Willem den Besten; Dirk Thierens; Peter A. N. Bosman (PPSN, 2016)

Exploiting linkage information in real-valued optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. - Anton Bouter; Tanja Alderliesten; Cees Witteveen; Peter A. N. Bosman (GECCO, 2017)

The multi-objective real-valued gene-pool optimal mixing evolutionary algorithm. - Anton Bouter; Ngoc Hoang Luong; Cees Witteveen; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2017)

Spatial redistribution of irregularly-spaced pareto fronts for more intuitive navigation and solution selection. - Anton Bouter; Kleopatra Pirpinia; Tanja Alderliesten; Peter A. N. Bosman (GECCO (Companion), 2017)

Efficient, effective, and insightful tackling of the high-dose-rate brachytherapy treatment planning problem for prostate cancer using evolutionary multi-objective optimization algorithms. - Ngoc Hoang Luong; Anton Bouter; Marjolein C. van der Meer; Yury Niatsetski; Cees Witteveen; Arjan Bel; Tanja Alderliesten; Peter A. N. Bosman (GECCO (Companion), 2017)

Niching an estimation-of-distribution algorithm by hierarchical Gaussian mixture learning. - S. C. Maree; Tanja Alderliesten; Dirk Thierens; Peter A. N. Bosman (GECCO, 2017)

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. - 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 (GECCO, 2017)

Model-based evolutionary algorithms: GECCO 2017 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2017)

Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning. - Marco Virgolin; Tanja Alderliesten; Cees Witteveen; Peter A. N. Bosman (GECCO, 2017)

A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality. - Anton Bouter; Tanja Alderliesten; Peter A. N. Bosman (Image Processing, 2017)

Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problems. - Anton Bouter; Tanja Alderliesten; Arjan Bel; Cees Witteveen; Peter A. N. Bosman (GECCO, 2018)

Improving the performance of MO-RV-GOMEA on problems with many objectives using tchebycheff scalarizations. - Ngoc Hoang Luong; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2018)

Real-valued evolutionary multi-modal optimization driven by hill-valley clustering. - S. C. Maree; Tanja Alderliesten; Dirk Thierens; Peter A. N. Bosman (GECCO, 2018)

Better and faster catheter position optimization in HDR brachytherapy for prostate cancer using multi-objective real-valued GOMEA. - Marjolein C. van der Meer; Bradley R. Pieters; Yury Niatsetski; Tanja Alderliesten; Arjan Bel; Peter A. N. Bosman (GECCO, 2018)

Learning bayesian network structures with GOMEA. - Kalia Orphanou; Dirk Thierens; Peter A. N. Bosman (GECCO, 2018)

Model-based evolutionary algorithms: GECCO 2018 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2018)

Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors. - Marco Virgolin; Tanja Alderliesten; Arjan Bel; Cees Witteveen; Peter A. N. Bosman (GECCO, 2018)

Heuristics in Permutation GOMEA for Solving the Permutation Flowshop Scheduling Problem. - G. H. Aalvanger; Ngoc Hoang Luong; Peter A. N. Bosman; Dirk Thierens (PPSN (1), 2018)

Benchmarking the Hill-Valley Evolutionary Algorithm for the GECCO 2018 Competition on Niching Methods Multimodal Optimization. - S. C. Maree; Tanja Alderliesten; Dirk Thierens; Peter A. N. Bosman (CoRR, 2018)

Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning. - Ngoc Hoang Luong; Han La Poutré; Peter A. N. Bosman (Evol. Comput., 2018)

GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems. - Krzysztof L. Sadowski; Dirk Thierens; Peter A. N. Bosman (Evol. Comput., 2018)

Unveiling evolutionary algorithm representation with DU maps. - Eric Medvet; Marco Virgolin; Mauro Castelli; Peter A. N. Bosman; Ivo Gonçalves; Tea Tusar (Genet. Program. Evolvable Mach., 2018)

The importance of implementation details and parameter settings in black-box optimization: a case study on Gaussian estimation-of-distribution algorithms and circles-in-a-square packing problems. - Peter A. N. Bosman; Marcus Gallagher (Soft Comput., 2018)

Application and benchmarking of multi-objective evolutionary algorithms on high-dose-rate brachytherapy planning for prostate cancer treatment. - Ngoc Hoang Luong; Tanja Alderliesten; Arjan Bel; Yury Niatsetski; Peter A. N. Bosman (Swarm Evol. Comput., 2018)

Multi-objective Gene-pool Optimal Mixing Evolutionary Algorithm with the Interleaved Multi-start Scheme. - Ngoc Hoang Luong; Han La Poutré; Peter A. N. Bosman (Swarm Evol. Comput., 2018)

Convolutional neural network surrogate-assisted GOMEA. - Arkadiy Dushatskiy; Adriënne M. Mendrik; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2019)

Real-valued evolutionary multi-modal multi-objective optimization by hill-valley clustering. - S. C. Maree; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2019)

Toward self-learning model-based EAs. - Erik A. Meulman; Peter A. N. Bosman (GECCO (Companion), 2019)

Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression. - Marco Virgolin; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2019)

Evolutionary multi-objective meta-optimization of deformation and tissue removal parameters improves the performance of deformable image registration of pre- and post-surgery images. - Kleopatra Pirpinia; Peter A. N. Bosman; Jan-Jakob Sonke; Marcel van Herk; Tanja Alderliesten (Image Processing, 2019)

Evolutionary Machine Learning for Multi-Objective Class Solutions in Medical Deformable Image Registration. - Kleopatra Pirpinia; Peter A. N. Bosman; Jan-Jakob Sonke; Marcel van Herk; Tanja Alderliesten (Algorithms, 2019)

Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy. - Ngoc Hoang Luong; Tanja Alderliesten; Bradley R. Pieters; Arjan Bel; Yury Niatsetski; Peter A. N. Bosman (Appl. Soft Comput., 2019)

A Model-based Genetic Programming Approach for Symbolic Regression of Small Expressions. - Marco Virgolin; Tanja Alderliesten; Cees Witteveen; Peter A. N. Bosman (CoRR, 2019)

Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization. - S. C. Maree; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2019)

Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms. - Marco Virgolin; Ziyuan Wang; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2019)

Leveraging conditional linkage models in gray-box optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. - Anton Bouter; Stefanus C. Maree; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2020)

Model-based evolutionary algorithms: GECCO 2020 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO Companion, 2020)

Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms. - Arkadiy Dushatskiy; Adriënne M. Mendrik; Peter A. N. Bosman; Tanja Alderliesten (Image Processing, 2020)

An end-to-end deep learning approach for landmark detection and matching in medical images. - Monika Grewal; Timo M. Deist; Jan Wiersma; Peter A. N. Bosman; Tanja Alderliesten (Image Processing, 2020)

Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent. - Timo M. Deist; Stefanus C. Maree; Tanja Alderliesten; Peter A. N. Bosman (PPSN (2), 2020)

Ensuring Smoothly Navigable Approximation Sets by Bézier Curve Parameterizations in Evolutionary Bi-objective Optimization. - Stefanus C. Maree; Tanja Alderliesten; Peter A. N. Bosman (PPSN (2), 2020)

Robust Evolutionary Bi-objective Optimization for Prostate Cancer Treatment with High-Dose-Rate Brachytherapy. - Marjolein C. van der Meer; Arjan Bel; Yury Niatsetski; Tanja Alderliesten; Bradley R. Pieters; Peter A. N. Bosman (PPSN (2), 2020)

Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy. - Marco Virgolin; Ziyuan Wang; Brian V. Balgobind; Irma W. E. M. van Dijk; Jan Wiersma; Petra S. Kroon; Geert O. R. Janssens; Marcel van Herk; D. C. Hodgson; L. Zadravec Zaletel; C. R. N. Rasch; Arjan Bel; et al. (CoRR, 2020)

Uncrowded Hypervolume-based Multi-objective Optimization with Gene-pool Optimal Mixing. - S. C. Maree; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2020)

Ensuring smoothly navigable approximation sets by Bezier curve parameterizations in evolutionary bi-objective optimization - applied to brachytherapy treatment planning for prostate cancer. - S. C. Maree; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2020)

On explaining machine learning models by evolving crucial and compact features. - Marco Virgolin; Tanja Alderliesten; Peter A. N. Bosman (Swarm Evol. Comput., 2020)

GPU-Accelerated Parallel Gene-pool Optimal Mixing Applied to Multi-Objective Deformable Image Registration. - Anton Bouter; Tanja Alderliesten; Peter A. N. Bosman (CEC, 2021)

Local Search is a Remarkably Strong Baseline for Neural Architecture Search. - Tom Den Ottelander; Arkadiy Dushatskiy; Marco Virgolin; Peter A. N. Bosman (EMO, 2021)

A novel surrogate-assisted evolutionary algorithm applied to partition-based ensemble learning. - Arkadiy Dushatskiy; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2021)

Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. - Michal Witold Przewozniczek; Marcin M. Komarnicki; Peter A. N. Bosman; Dirk Thierens; Bartosz Frej; Ngoc Hoang Luong (GECCO Companion, 2021)

Optimization of multi-objective mixed-integer problems with a model-based evolutionary algorithm in a black-box setting. - Krzysztof L. Sadowski; Dirk Thierens; Peter A. N. Bosman (GECCO Companion, 2021)

Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization. - Timo M. Deist; Monika Grewal; Frank J. W. M. Dankers; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2021)

Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration. - Monika Grewal; Jan Wiersma; Henrike Westerveld; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2021)

Achieving Highly Scalable Evolutionary Real-Valued Optimization by Exploiting Partial Evaluations. - Anton Bouter; Tanja Alderliesten; Peter A. N. Bosman (Evol. Comput., 2021)

Improving Model-Based Genetic Programming for Symbolic Regression of Small Expressions. - Marco Virgolin; Tanja Alderliesten; Cees Witteveen; Peter A. N. Bosman (Evol. Comput., 2021)

Fitness-Based Linkage Learning in the Real-Valued Gene-Pool Optimal Mixing Evolutionary Algorithm. - Chantal Olieman; Anton Bouter; Peter A. N. Bosman (IEEE Trans. Evol. Comput., 2021)

A Novel Approach to Designing Surrogate-assisted Genetic Algorithms by Combining Efficient Learning of Walsh Coefficients and Dependencies. - Arkadiy Dushatskiy; Tanja Alderliesten; Peter A. N. Bosman (ACM Trans. Evol. Learn. Optim., 2021)

Two-Phase Real-Valued Multimodal Optimization with the Hill-Valley Evolutionary Algorithm. - Stefanus C. Maree; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Metaheuristics for Finding Multiple Solutions, 2021)

GPU-accelerated parallel gene-pool optimal mixing in a gray-box optimization setting. - Anton Bouter; Peter A. N. Bosman (GECCO, 2022)

Evolutionary neural cascade search across supernetworks. - Alexander Chebykin; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2022)

Adaptive objective configuration in bi-objective evolutionary optimization for cervical cancer brachytherapy treatment planning. - Leah R. M. Dickhoff; Ellen M. Kerkhof; Heloisa H. Deuzeman; Carien L. Creutzberg; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2022)

Heed the noise in performance evaluations in neural architecture search. - Arkadiy Dushatskiy; Tanja Alderliesten; Peter A. N. Bosman (GECCO Companion, 2022)

Solving multi-structured problems by introducing linkage kernels into GOMEA. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2022)

Evolvability degeneration in multi-objective genetic programming for symbolic regression. - Dazhuang Liu; Marco Virgolin; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2022)

Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models. - E. M. C. Sijben; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2022)

Model-based evolutionary algorithms: GECCO 2022 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO Companion, 2022)

On genetic programming representations and fitness functions for interpretable dimensionality reduction. - Thomas Uriot; Marco Virgolin; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2022)

Coefficient mutation in the gene-pool optimal mixing evolutionary algorithm for symbolic regression. - Marco Virgolin; Peter A. N. Bosman (GECCO Companion, 2022)

Multi-objective dual simplex-mesh based deformable image registration for 3D medical images - proof of concept. - Georgios Andreadis; Peter A. N. Bosman; Tanja Alderliesten (Image Processing, 2022)

Mixed-block neural architecture search for medical image segmentation. - Martijn M. A. Bosma; Arkadiy Dushatskiy; Monika Grewal; Tanja Alderliesten; Peter A. N. Bosman (Image Processing, 2022)

Data variation-aware medical image segmentation. - Arkadiy Dushatskiy; Gerry Lowe; Peter A. N. Bosman; Tanja Alderliesten (Image Processing, 2022)

Hybridizing Hypervolume-Based Evolutionary Algorithms and Gradient Descent by Dynamic Resource Allocation. - Damy M. F. Ha; Timo M. Deist; Peter A. N. Bosman (PPSN (2), 2022)

Gene-pool Optimal Mixing in Cartesian Genetic Programming. - Joe Harrison; Tanja Alderliesten; Peter A. N. Bosman (PPSN (2), 2022)

Obtaining Smoothly Navigable Approximation Sets in Bi-objective Multi-modal Optimization. - Renzo J. Scholman; Anton Bouter; Leah R. M. Dickhoff; Tanja Alderliesten; Peter A. N. Bosman (PPSN (2), 2022)

Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning. - Marco Virgolin; Andrea De Lorenzo; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2022)

Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning. - Marco Virgolin; Eric Medvet; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2022)

Uncrowded Hypervolume-Based Multiobjective Optimization with Gene-Pool Optimal Mixing. - S. C. Maree; Tanja Alderliesten; Peter A. N. Bosman (Evol. Comput., 2022)

On the impact of linkage learning, gene-pool optimal mixing, and non-redundant encoding on permutation optimization. - Arthur Guijt; Ngoc Hoang Luong; Peter A. N. Bosman; Mathijs de Weerdt (Swarm Evol. Comput., 2022)

Solving multi-structured problems by introducing linkage kernels into GOMEA - Source Code. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2022)

Shrink-Perturb Improves Architecture Mixing During Population Based Training for Neural Architecture Search. - Alexander Chebykin; Arkadiy Dushatskiy; Tanja Alderliesten; Peter A. N. Bosman (ECAI, 2023)

Multi-objective Learning Using HV Maximization. - Timo M. Deist; Monika Grewal; Frank J. W. M. Dankers; Tanja Alderliesten; Peter A. N. Bosman (EMO, 2023)

MOREA: a GPU-accelerated Evolutionary Algorithm for Multi-Objective Deformable Registration of 3D Medical Images. - Georgios Andreadis; Peter A. N. Bosman; Tanja Alderliesten (GECCO, 2023)

A Joint Python/C++ Library for Efficient yet Accessible Black-Box and Gray-Box Optimization with GOMEA. - Anton Bouter; Peter A. N. Bosman (GECCO Companion, 2023)

The Impact of Asynchrony on Parallel Model-Based EAs. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2023)

Mini-Batching, Gradient-Clipping, First- versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression? - Joe Harrison; Marco Virgolin; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2023)

Multi-Objective Population Based Training. - Arkadiy Dushatskiy; Alexander Chebykin; Tanja Alderliesten; Peter A. N. Bosman (ICML, 2023)

Learning Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations. - Monika Grewal; Dustin van Weersel; Henrike Westerveld; Peter A. N. Bosman; Tanja Alderliesten (MIDL, 2023)

Bi-objective optimization of organ properties for the simulation of intracavitary brachytherapy applicator placement in cervical cancer. - Cedric J. Rodriguez; Stephanie M. de Boer; Peter A. N. Bosman; Tanja Alderliesten (Image-Guided Procedures, 2023)

Convolutions, transformers, and their ensembles for the segmentation of organs at risk in radiation treatment of cervical cancer. - Vangelis Kostoulas; Peter A. N. Bosman; Tanja Alderliesten (Image Processing, 2023)

Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations. - Monika Grewal; Dustin van Weersel; Henrike Westerveld; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2023)

Challenges in Benchmarking Optimization Heuristics (Dagstuhl Seminar 23251). - Anne Auger; Peter A. N. Bosman; Pascal Kerschke; Darrell Whitley; Lennart Schäpermeier (Dagstuhl Reports, 2023)

Impact of Asynchrony on MBEAs - Source Code. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2023)

Fitness-based Linkage Learning and Maximum-Clique Conditional Linkage Modelling for Gray-box Optimization with RV-GOMEA. - Georgios Andreadis; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2024)

Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (GECCO Companion, 2024)

Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation. - Cedric J. Rodriguez; Sarah L. Thomson; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2024)

Improving the efficiency of GP-GOMEA for higher-arity operators. - Thalea Schlender; Mafalda Malafaia; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2024)

Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals. - Evi Sijben; Jeroen C. Jansen; Peter A. N. Bosman; Tanja Alderliesten (GECCO, 2024)

Hyperparameter-Free Medical Image Synthesis for Sharing Data and Improving Site-Specific Segmentation. - Alexander Chebykin; Peter A. N. Bosman; Tanja Alderliesten (MIDL, 2024)

Multi-Objective Learning for Deformable Image Registration. - Monika Grewal; Henrike Westerveld; Peter A. N. Bosman; Tanja Alderliesten (MIDL, 2024)

Learning Discretized Bayesian Networks with GOMEA. - Damy M. F. Ha; Tanja Alderliesten; Peter A. N. Bosman (PPSN (3), 2024)

Simultaneous Model-Based Evolution of Constants and Expression Structure in GP-GOMEA for Symbolic Regression. - Johannes Koch; Tanja Alderliesten; Peter A. N. Bosman (PPSN (1), 2024)

Balancing Between Time Budgets and Costs in Surrogate-Assisted Evolutionary Algorithms. - Cedric J. Rodriguez; Peter A. N. Bosman; Tanja Alderliesten (PPSN (2), 2024)

A Tournament of Transformation Models: B-Spline-based vs. Mesh-based Multi-Objective Deformable Image Registration. - Georgios Andreadis; Joas I. Mulder; Anton Bouter; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2024)

MultiFIX: An XAI-friendly feature inducing approach to building models from multimodal data. - Mafalda Malafaia; Thalea Schlender; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2024)

Stitching for Neuroevolution: Recombining Deep Neural Networks without Breaking Them. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2024)

Deep learning-based auto-segmentation of paraganglioma for growth monitoring. - E. M. C. Sijben; Jeroen C. Jansen; M. de Ridder; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2024)

Parameterless Gene-Pool Optimal Mixing Evolutionary Algorithms. - Arkadiy Dushatskiy; Marco Virgolin; Anton Bouter; Dirk Thierens; Peter A. N. Bosman (Evol. Comput., 2024)

Software for the paper: Temporal true and surrogate fitness landscape analysis for expensive bi-objective optimisation. - Cedric J. Rodriguez; Sarah L. Thomson; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2024)

Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching - Source Code. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2024)

Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching - Results Data. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2024)

More Efficient Real-Valued Gray-Box Optimization through Incremental Distribution Estimation in RV-GOMEA. - Renzo J. Scholman; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2025)

To Be Greedy, or Not to Be - That Is the Question for Population Based Training Variants. - Alexander Chebykin; Tanja Alderliesten; Peter A. N. Bosman (Trans. Mach. Learn. Res., 2025)

Multi-Objective Deep-Learning-based Biomechanical Deformable Image Registration with MOREA. - Georgios Andreadis; Eduard Ruiz Munné; Thomas H. W. Bäck; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2025)

Thinking Outside the Template with Modular GP-GOMEA. - Joe Harrison; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2025)

A Step towards Interpretable Multimodal AI Models with MultiFIX. - Mafalda Malafaia; Thalea Schlender; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2025)

The Pitfalls and Potentials of Adding Gene-invariance to Optimal Mixing. - Anton Bouter; Dirk Thierens; Peter A. N. Bosman (CoRR, 2025)

A Better Multi-Objective GP-GOMEA - But do we Need it? - Joe Harrison; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2025)

Dealing with Segmentation Errors in Needle Reconstruction for MRI-Guided Brachytherapy. - Vangelis Kostoulas; Arthur Guijt; Ellen M. Kerkhof; Bradley R. Pieters; Peter A. N. Bosman; Tanja Alderliesten (CoRR, 2025)