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2020 – today
- 2024
[c71]Georgios Andreadis
, Tanja Alderliesten, Peter A. N. Bosman:
Fitness-based Linkage Learning and Maximum-Clique Conditional Linkage Modelling for Gray-box Optimization with RV-GOMEA. GECCO 2024- [c70]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 - [c69]Cedric J. Rodriguez, Sarah L. Thomson, Tanja Alderliesten, Peter A. N. Bosman:
Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation. GECCO 2024 - [c68]Thalea Schlender, Mafalda Malafaia, Tanja Alderliesten, Peter A. N. Bosman:
Improving the efficiency of GP-GOMEA for higher-arity operators. GECCO 2024 - [c67]Evi Sijben, Jeroen C. Jansen, Peter A. N. Bosman, Tanja Alderliesten:
Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals. GECCO 2024 - [c66]Johannes Koch, Tanja Alderliesten, Peter A. N. Bosman:
Simultaneous Model-Based Evolution of Constants and Expression Structure in GP-GOMEA for Symbolic Regression. PPSN (1) 2024: 238-255 - [c65]Cedric J. Rodriguez, Peter A. N. Bosman, Tanja Alderliesten:
Balancing Between Time Budgets and Costs in Surrogate-Assisted Evolutionary Algorithms. PPSN (2) 2024: 322-339 - [c64]Damy M. F. Ha, Tanja Alderliesten, Peter A. N. Bosman:
Learning Discretized Bayesian Networks with GOMEA. PPSN (3) 2024: 352-368 - [d5]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching - Source Code. Zenodo, 2024
- [d4]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching - Results Data. Zenodo, 2024 - [d3]Cedric J. Rodriguez, Sarah L. Thomson, Tanja Alderliesten, Peter A. N. Bosman:
Software for the paper: Temporal true and surrogate fitness landscape analysis for expensive bi-objective optimisation. Zenodo, 2024 - [i45]Georgios Andreadis, Joas I. Mulder, Anton Bouter, Peter A. N. Bosman, Tanja Alderliesten:
A Tournament of Transformation Models: B-Spline-based vs. Mesh-based Multi-Objective Deformable Image Registration. CoRR abs/2401.16867 (2024) - [i44]Thalea Schlender, Mafalda Malafaia, Tanja Alderliesten, Peter A. N. Bosman:
Improving the efficiency of GP-GOMEA for higher-arity operators. CoRR abs/2402.09854 (2024) - [i43]Georgios Andreadis, Tanja Alderliesten, Peter A. N. Bosman:
Fitness-based Linkage Learning and Maximum-Clique Conditional Linkage Modelling for Gray-box Optimization with RV-GOMEA. CoRR abs/2402.10757 (2024) - [i42]Damy M. F. Ha, Tanja Alderliesten, Peter A. N. Bosman:
Learning Discretized Bayesian Networks with GOMEA. CoRR abs/2402.12175 (2024) - [i41]Mafalda Malafaia, Thalea Schlender, Peter A. N. Bosman, Tanja Alderliesten:
MultiFIX: An XAI-friendly feature inducing approach to building models from multimodal data. CoRR abs/2402.12183 (2024) - [i40]E. M. C. Sijben, Jeroen C. Jansen, Peter A. N. Bosman, Tanja Alderliesten:
Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals. CoRR abs/2402.12510 (2024) - [i39]Monika Grewal, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten:
Multi-Objective Learning for Deformable Image Registration. CoRR abs/2402.16658 (2024) - [i38]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) - [i37]Alexander Chebykin, Peter A. N. Bosman, Tanja Alderliesten:
Hyperparameter-Free Medical Image Synthesis for Sharing Data and Improving Site-Specific Segmentation. CoRR abs/2404.06240 (2024) - [i36]Cedric J. Rodriguez, Sarah L. Thomson, Tanja Alderliesten, Peter A. N. Bosman:
Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation. CoRR abs/2404.06557 (2024) - [i35]E. M. C. Sijben, Jeroen C. Jansen, M. de Ridder, Peter A. N. Bosman, Tanja Alderliesten:
Deep learning-based auto-segmentation of paraganglioma for growth monitoring. CoRR abs/2404.07952 (2024) - 2023
- [c63]Alexander Chebykin, Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
Shrink-Perturb Improves Architecture Mixing During Population Based Training for Neural Architecture Search. ECAI 2023: 381-388 - [c62]Timo M. Deist, Monika Grewal, Frank J. W. M. Dankers, Tanja Alderliesten, Peter A. N. Bosman:
Multi-objective Learning Using HV Maximization. EMO 2023: 103-117 - [c61]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
The Impact of Asynchrony on Parallel Model-Based EAs. GECCO 2023: 910-918 - [c60]Joe Harrison, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
Mini-Batching, Gradient-Clipping, First- versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression? GECCO 2023: 1127-1136 - [c59]Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten:
MOREA: a GPU-accelerated Evolutionary Algorithm for Multi-Objective Deformable Registration of 3D Medical Images. GECCO 2023: 1294-1302 - [c58]Arkadiy Dushatskiy, Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman:
Multi-Objective Population Based Training. ICML 2023: 8969-8989 - [c57]Monika Grewal, Dustin van Weersel, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten:
Learning Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations. MIDL 2023: 260-273 - [c56]Cedric J. Rodriguez, Stephanie M. de Boer, Peter A. N. Bosman, Tanja Alderliesten:
Bi-objective optimization of organ properties for the simulation of intracavitary brachytherapy applicator placement in cervical cancer. Image-Guided Procedures 2023 - [c55]Vangelis Kostoulas, Peter A. N. Bosman, Tanja Alderliesten:
Convolutions, transformers, and their ensembles for the segmentation of organs at risk in radiation treatment of cervical cancer. Image Processing 2023 - [d2]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Impact of Asynchrony on MBEAs - Source Code. Zenodo, 2023 - [i34]Monika Grewal, Dustin van Weersel, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten:
Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations. CoRR abs/2302.10661 (2023) - [i33]Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten:
MOREA: a GPU-accelerated Evolutionary Algorithm for Multi-Objective Deformable Registration of 3D Medical Images. CoRR abs/2303.04873 (2023) - [i32]Vangelis Kostoulas, Peter A. N. Bosman, Tanja Alderliesten:
Convolutions, Transformers, and their Ensembles for the Segmentation of Organs at Risk in Radiation Treatment of Cervical Cancer. CoRR abs/2303.11501 (2023) - [i31]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
The Impact of Asynchrony on Parallel Model-Based EAs. CoRR abs/2303.15543 (2023) - [i30]Arkadiy Dushatskiy, Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman:
Multi-Objective Population Based Training. CoRR abs/2306.01436 (2023) - [i29]Alexander Chebykin, Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
Shrink-Perturb Improves Architecture Mixing during Population Based Training for Neural Architecture Search. CoRR abs/2307.15621 (2023) - 2022
- [j13]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Uncrowded Hypervolume-Based Multiobjective Optimization with Gene-Pool Optimal Mixing. Evol. Comput. 30(3): 329-353 (2022) - [c54]E. M. C. Sijben, Tanja Alderliesten, Peter A. N. Bosman:
Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models. GECCO 2022: 440-448 - [c53]Thomas Uriot, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
On genetic programming representations and fitness functions for interpretable dimensionality reduction. GECCO 2022: 458-466 - [c52]Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
Solving multi-structured problems by introducing linkage kernels into GOMEA. GECCO 2022: 703-711 - [c51]Dazhuang Liu, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
Evolvability degeneration in multi-objective genetic programming for symbolic regression. GECCO 2022: 973-981 - [c50]Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman:
Evolutionary neural cascade search across supernetworks. GECCO 2022: 1038-1047 - [c49]Leah R. M. Dickhoff, Ellen M. Kerkhof, Heloisa H. Deuzeman, Carien L. Creutzberg, Tanja Alderliesten, Peter A. N. Bosman:
Adaptive objective configuration in bi-objective evolutionary optimization for cervical cancer brachytherapy treatment planning. GECCO 2022: 1173-1181 - [c48]Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
Heed the noise in performance evaluations in neural architecture search. GECCO Companion 2022: 2104-2112 - [c47]Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten:
Multi-objective dual simplex-mesh based deformable image registration for 3D medical images - proof of concept. Image Processing 2022 - [c46]Martijn M. A. Bosma, Arkadiy Dushatskiy, Monika Grewal, Tanja Alderliesten, Peter A. N. Bosman:
Mixed-block neural architecture search for medical image segmentation. Image Processing 2022 - [c45]Arkadiy Dushatskiy, Gerry Lowe, Peter A. N. Bosman, Tanja Alderliesten:
Data variation-aware medical image segmentation. Image Processing 2022 - [c44]Joe Harrison, Tanja Alderliesten, Peter A. N. Bosman:
Gene-pool Optimal Mixing in Cartesian Genetic Programming. PPSN (2) 2022: 19-32 - [c43]Renzo J. Scholman, Anton Bouter, Leah R. M. Dickhoff, Tanja Alderliesten, Peter A. N. Bosman:
Obtaining Smoothly Navigable Approximation Sets in Bi-objective Multi-modal Optimization. PPSN (2) 2022: 247-262 - [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 - [i28]Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
Heed the Noise in Performance Evaluations in Neural Architecture Search. CoRR abs/2202.02078 (2022) - [i27]Marco Virgolin, Andrea De Lorenzo, Tanja Alderliesten, Peter A. N. Bosman:
Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning. CoRR abs/2202.05187 (2022) - [i26]Dazhuang Liu, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
Evolvability Degeneration in Multi-Objective Genetic Programming for Symbolic Regression. CoRR abs/2202.06983 (2022) - [i25]Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten:
Multi-Objective Dual Simplex-Mesh Based Deformable Image Registration for 3D Medical Images - Proof of Concept. CoRR abs/2202.11001 (2022) - [i24]Martijn M. A. Bosma, Arkadiy Dushatskiy, Monika Grewal, Tanja Alderliesten, Peter A. N. Bosman:
Mixed-Block Neural Architecture Search for Medical Image Segmentation. CoRR abs/2202.11401 (2022) - [i23]Arkadiy Dushatskiy, Gerry Lowe, Peter A. N. Bosman, Tanja Alderliesten:
Data variation-aware medical image segmentation. CoRR abs/2202.12099 (2022) - [i22]Thomas Uriot, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
On genetic programming representations and fitness functions for interpretable dimensionality reduction. CoRR abs/2203.00528 (2022) - [i21]Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman:
Evolutionary Neural Cascade Search across Supernetworks. CoRR abs/2203.04011 (2022) - [i20]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) - [i19]Leah R. M. Dickhoff, Ellen M. Kerkhof, Heloisa H. Deuzeman, Carien L. Creutzberg, Tanja Alderliesten, Peter A. N. Bosman:
Adaptive Objective Configuration in Bi-Objective Evolutionary Optimization for Cervical Cancer Brachytherapy Treatment Planning. CoRR abs/2203.08851 (2022) - [i18]Renzo J. Scholman, Anton Bouter, Leah R. M. Dickhoff, Tanja Alderliesten, Peter A. N. Bosman:
Obtaining Smoothly Navigable Approximation Sets in Bi-Objective Multi-Modal Optimization. CoRR abs/2203.09214 (2022) - [i17]E. M. C. Sijben, Tanja Alderliesten, Peter A. N. Bosman:
Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models. CoRR abs/2203.13347 (2022) - [i16]Marco Virgolin, Eric Medvet, Tanja Alderliesten, Peter A. N. Bosman:
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning. CoRR abs/2204.02046 (2022) - 2021
- [j12]Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman:
Achieving Highly Scalable Evolutionary Real-Valued Optimization by Exploiting Partial Evaluations. Evol. Comput. 29(1): 129-155 (2021) - [j11]Marco Virgolin, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
Improving Model-Based Genetic Programming for Symbolic Regression of Small Expressions. Evol. Comput. 29(2): 211-237 (2021) - [j10]Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
A Novel Approach to Designing Surrogate-assisted Genetic Algorithms by Combining Efficient Learning of Walsh Coefficients and Dependencies. ACM Trans. Evol. Learn. Optim. 1(2): 5:1-5:23 (2021) - [c42]Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman:
GPU-Accelerated Parallel Gene-pool Optimal Mixing Applied to Multi-Objective Deformable Image Registration. CEC 2021: 2539-2548 - [c41]Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
A novel surrogate-assisted evolutionary algorithm applied to partition-based ensemble learning. GECCO 2021: 583-591 - [p1]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 - [i15]Timo M. Deist, Monika Grewal, Frank J. W. M. Dankers, Tanja Alderliesten, Peter A. N. Bosman:
Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization. CoRR abs/2102.04523 (2021) - [i14]Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
A Novel Surrogate-assisted Evolutionary Algorithm Applied to Partition-based Ensemble Learning. CoRR abs/2104.08048 (2021) - [i13]Monika Grewal, Jan Wiersma, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten:
Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration. CoRR abs/2109.02722 (2021) - 2020
- [j9]Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
On explaining machine learning models by evolving crucial and compact features. Swarm Evol. Comput. 53: 100640 (2020) - [c40]Anton Bouter, Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Leveraging conditional linkage models in gray-box optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2020: 603-611 - [c39]Arkadiy Dushatskiy, Adriënne M. Mendrik, Peter A. N. Bosman, Tanja Alderliesten:
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms. Image Processing 2020: 113131B - [c38]Monika Grewal, Timo M. Deist, Jan Wiersma, Peter A. N. Bosman, Tanja Alderliesten:
An end-to-end deep learning approach for landmark detection and matching in medical images. Image Processing 2020: 1131328 - [c37]Timo M. Deist, Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent. PPSN (2) 2020: 186-200 - [c36]Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Ensuring Smoothly Navigable Approximation Sets by Bézier Curve Parameterizations in Evolutionary Bi-objective Optimization. PPSN (2) 2020: 215-228 - [c35]Marjolein C. van der Meer, Arjan Bel, Yury Niatsetski, Tanja Alderliesten, Bradley R. Pieters, Peter A. N. Bosman:
Robust Evolutionary Bi-objective Optimization for Prostate Cancer Treatment with High-Dose-Rate Brachytherapy. PPSN (2) 2020: 441-453 - [i12]Monika Grewal, Timo M. Deist, Jan Wiersma, Peter A. N. Bosman, Tanja Alderliesten:
An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical Images. CoRR abs/2001.07434 (2020) - [i11]Arkadiy Dushatskiy, Adriënne M. Mendrik, Peter A. N. Bosman, Tanja Alderliesten:
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms. CoRR abs/2001.08552 (2020) - [i10]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, Peter A. N. Bosman, Tanja Alderliesten:
Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy. CoRR abs/2002.07161 (2020) - [i9]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Uncrowded Hypervolume-based Multi-objective Optimization with Gene-pool Optimal Mixing. CoRR abs/2004.05068 (2020) - [i8]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Ensuring smoothly navigable approximation sets by Bezier curve parameterizations in evolutionary bi-objective optimization - applied to brachytherapy treatment planning for prostate cancer. CoRR abs/2006.06449 (2020) - [i7]Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Real-valued Evolutionary Multi-modal Multi-objective Optimization by Hill-Valley Clustering. CoRR abs/2010.14998 (2020)
2010 – 2019
- 2019
- [j8]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk, Tanja Alderliesten:
Evolutionary Machine Learning for Multi-Objective Class Solutions in Medical Deformable Image Registration. Algorithms 12(5): 99 (2019) - [j7]Ngoc Hoang Luong, Tanja Alderliesten, Bradley R. Pieters, Arjan Bel, Yury Niatsetski, Peter A. N. Bosman:
Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy. Appl. Soft Comput. 84 (2019) - [c34]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Real-valued evolutionary multi-modal multi-objective optimization by hill-valley clustering. GECCO 2019: 568-576 - [c33]Arkadiy Dushatskiy, Adriënne M. Mendrik, Tanja Alderliesten, Peter A. N. Bosman:
Convolutional neural network surrogate-assisted GOMEA. GECCO 2019: 753-761 - [c32]Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression. GECCO 2019: 1084-1092 - [c31]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk, Tanja Alderliesten:
Evolutionary multi-objective meta-optimization of deformation and tissue removal parameters improves the performance of deformable image registration of pre- and post-surgery images. Image Processing 2019: 1094939 - [i6]Marco Virgolin, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
A Model-based Genetic Programming Approach for Symbolic Regression of Small Expressions. CoRR abs/1904.02050 (2019) - [i5]Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
On Explaining Machine Learning Models by Evolving Crucial and Compact Features. CoRR abs/1907.02260 (2019) - [i4]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization. CoRR abs/1907.10988 (2019) - [i3]Marco Virgolin, Ziyuan Wang, Tanja Alderliesten, Peter A. N. Bosman:
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms. CoRR abs/1909.03723 (2019) - 2018
- [j6]Ngoc Hoang Luong, Tanja Alderliesten, Arjan Bel, Yury Niatsetski, Peter A. N. Bosman:
Application and benchmarking of multi-objective evolutionary algorithms on high-dose-rate brachytherapy planning for prostate cancer treatment. Swarm Evol. Comput. 40: 37-52 (2018) - [c30]Ngoc Hoang Luong, Tanja Alderliesten, Peter A. N. Bosman:
Improving the performance of MO-RV-GOMEA on problems with many objectives using tchebycheff scalarizations. GECCO 2018: 705-712 - [c29]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 - [c28]Anton Bouter, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman:
Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problems. GECCO 2018: 1199-1206 - [c27]Marjolein C. van der Meer, Bradley R. Pieters, Yury Niatsetski, Tanja Alderliesten, Arjan Bel, Peter A. N. Bosman:
Better and faster catheter position optimization in HDR brachytherapy for prostate cancer using multi-objective real-valued GOMEA. GECCO 2018: 1387-1394 - [c26]Marco Virgolin, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman:
Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors. GECCO 2018: 1395-1402 - [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
- [c25]Anton Bouter, Ngoc Hoang Luong, Cees Witteveen, Tanja Alderliesten, Peter A. N. Bosman:
The multi-objective real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2017: 537-544 - [c24]Anton Bouter, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
Exploiting linkage information in real-valued optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2017: 705-712 - [c23]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 - [c22]Marco Virgolin, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning. GECCO 2017: 1041-1048 - [c21]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 - [c20]Ngoc Hoang Luong, Anton Bouter, Marjolein C. van der Meer, Yury Niatsetski, Cees Witteveen, Arjan Bel, Tanja Alderliesten, Peter A. N. Bosman:
Efficient, effective, and insightful tackling of the high-dose-rate brachytherapy treatment planning problem for prostate cancer using evolutionary multi-objective optimization algorithms. GECCO (Companion) 2017: 1372-1379 - [c19]Anton Bouter, Kleopatra Pirpinia, Tanja Alderliesten, Peter A. N. Bosman:
Spatial redistribution of irregularly-spaced pareto fronts for more intuitive navigation and solution selection. GECCO (Companion) 2017: 1697-1704 - [c18]Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman:
A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality. Image Processing 2017: 1013312 - 2016
- [j5]Tanja Alderliesten, Jill B. De Vis, Petra M. A. Lemmers, Frank van Bel, Manon J. N. L. Benders, Jeroen Hendrikse, Esben Thade Petersen:
T2-prepared velocity selective labelling: A novel idea for full-brain mapping of oxygen saturation. NeuroImage 139: 65-73 (2016) - [c17]Peng Jin, Niek van Wieringen, Maarten C. C. M. Hulshof, Arjan Bel, Tanja Alderliesten:
4D cone-beam CT imaging for guidance in radiation therapy: setup verification by use of implanted fiducial markers. Image-Guided Procedures 2016: 97862N - [c16]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk, Tanja Alderliesten:
A first step toward uncovering the truth about weight tuning in deformable image registration. Image Processing 2016: 978445 - [c15]Peter A. N. Bosman, Tanja Alderliesten:
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. Image Processing 2016: 978447 - 2015
- [c14]Kleopatra Pirpinia, Tanja Alderliesten, Jan-Jakob Sonke, Marcel van Herk, Peter A. N. Bosman:
Diversifying Multi-Objective Gradient Techniques and their Role in Hybrid Multi-Objective Evolutionary Algorithms for Deformable Medical Image Registration. GECCO 2015: 1255-1262 - [c13]Tanja Alderliesten, Peter A. N. Bosman, Arjan Bel:
Getting the most out of additional guidance information in deformable image registration by leveraging multi-objective optimization. Image Processing 2015: 94131R - [c12]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk, Tanja Alderliesten:
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. Image Processing 2015: 941339 - 2014
- [j4]Tanja Alderliesten, Jill B. De Vis, Petra M. A. Lemmers, Frank van Bel, Manon J. N. L. Benders, Jeroen Hendrikse, E. T. Petersen:
Simultaneous quantitative assessment of cerebral physiology using respiratory-calibrated MRI and near-infrared spectroscopy in healthy adults. NeuroImage 85: 255-263 (2014) - [j3]Jill B. De Vis, E. T. Petersen, Tanja Alderliesten, Floris Groenendaal, Linda S. de Vries, Frank van Bel, Manon J. N. L. Benders, Jeroen Hendrikse:
Non-invasive MRI measurements of venous oxygenation, oxygen extraction fraction and oxygen consumption in neonates. NeuroImage 95: 185-192 (2014) - [c11]Tanja Alderliesten, Peter A. N. Bosman, Jan-Jakob Sonke, Arjan Bel:
A multi-resolution strategy for a multi-objective deformable image registration framework that accommodates large anatomical differences. Image Processing 2014: 90343G - 2013
- [c10]Tanja Alderliesten, Anja Betgen, Corine van Vliet-Vroegindeweij, Peter Remeijer:
Validation of 3D surface imaging in breath-hold radiotherapy for breast cancer: one central camera unit versus three camera units. Image-Guided Procedures 2013: 86710F - [c9]Tanja Alderliesten, Anja Betgen, Corine van Vliet-Vroegindeweij, Peter Remeijer:
3D surface imaging for guidance in breast cancer radiotherapy: organs at risk. Image-Guided Procedures 2013: 86710G - [c8]Tanja Alderliesten, Jan-Jakob Sonke, Peter A. N. Bosman:
Deformable image registration by multi-objective optimization using a dual-dynamic transformation model to account for large anatomical differences. Image Processing 2013: 866910 - 2012
- [c7]Peter A. N. Bosman, Tanja Alderliesten:
Incremental gaussian model-building in multi-objective EDAs with an application to deformable image registration. GECCO 2012: 241-248 - [c6]Tanja Alderliesten, Jan-Jakob Sonke, Anja Betgen, Joeri Honnef, Corine van Vliet-Vroegindeweij, Peter Remeijer:
Application of 3D surface imaging in breast cancer radiotherapy. Image-Guided Procedures 2012: 83160A - [c5]Tanja Alderliesten, Jan-Jakob Sonke, Peter A. N. Bosman:
Multi-objective optimization for deformable image registration: proof of concept. Image Processing 2012: 831420
2000 – 2009
- 2009
- [c4]Tanja Alderliesten, Claudette Loo, Angelique T. E. F. Schlief, Anita Paape, Michiel van der Meer, Kenneth G. A. Gilhuijs:
Application of an image-guided navigation system in breast cancer localization. Image-Guided Procedures 2009: 726111 - 2007
- [j2]Tanja Alderliesten, Maurits K. Konings, Wiro J. Niessen:
Modeling Friction, Intrinsic Curvature, and Rotation of Guide Wires for Simulation of Minimally Invasive Vascular Interventions. IEEE Trans. Biomed. Eng. 54(1): 29-38 (2007) - [j1]Tanja Alderliesten, Peter A. N. Bosman, Wiro J. Niessen:
Towards a Real-Time Minimally-Invasive Vascular Intervention Simulation System. IEEE Trans. Medical Imaging 26(1): 128-132 (2007) - 2005
- [c3]Peter A. N. Bosman, Tanja Alderliesten:
Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions. GECCO Workshops 2005: 125-132 - 2002
- [c2]Tanja Alderliesten, Maurits K. Konings, Wiro J. Niessen:
Simulation of Guide Wire Propagation for Minimally Invasive Vascular Interventions. MICCAI (2) 2002: 245-252 - 2001
- [c1]Tanja Alderliesten, Wiro J. Niessen, Koen L. Vincken, J. B. Antoine Maintz, Floor Jansen, Onno van Nieuwenhuizen, Max A. Viergever:
Objective and reproducible segmentation and quantification of tuberous sclerosis lesions in FLAIR brain MR images. Image Processing 2001
Coauthor Index
[c71] [c70] [c69] [c68] [c67] [c66] [c65] [c64] [d5] [d4] [d3] [i45] [i44] [i43] [i42] [i41] [i40] [i39] [i38] [i37] [i36] [i35] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [c55] [d2] [i34] [i33] [i32] [i31] [i30] [i29] [j13] [c54] [c53] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [d1] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [j12] [j11] [j10] [c42] [c41] [p1] [i15] [i14] [i13] [j9] [c40] [c39] [c38] [c37] [c36] [c35] [i12] [i11] [i10] [i9] [i8] [i7] [j8] [j7] [c34] [c33] [c32] [c31] [i6] [i5] [i4] [i3] [j6] [c30] [c29] [c28] [c27] [c26] [i2] [i1] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c16] [c15] [c14] [c13] [c12] [c11] [c8] [c7] [c5] [j1] [c3]
Stefanus C. Maree
aka: S. C. Maree
aka: S. C. Maree
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