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07/28/2023
Shrink-Perturb Improves Architecture Mixing during Population Based Training for Neural Architecture Search
In this work, we show that simultaneously training and mixing neural net...
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06/02/2023
Multi-Objective Population Based Training
Population Based Training (PBT) is an efficient hyperparameter optimizat...
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03/27/2023
The Impact of Asynchrony on Parallel Model-Based EAs
In a parallel EA one can strictly adhere to the generational clock, and ...
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03/20/2023
Convolutions, Transformers, and their Ensembles for the Segmentation of Organs at Risk in Radiation Treatment of Cervical Cancer
Segmentation of regions of interest in images of patients, is a crucial ...
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03/08/2023
MOREA: a GPU-accelerated Evolutionary Algorithm for Multi-Objective Deformable Registration of 3D Medical Images
Finding a realistic deformation that transforms one image into another, ...
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02/21/2023
Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations
Deep learning models benefit from training with a large dataset (labeled...
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04/05/2022
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning
Interpretability can be critical for the safe and responsible use of mac...
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03/17/2022
Obtaining Smoothly Navigable Approximation Sets in Bi-Objective Multi-Modal Optimization
Even if a Multi-modal Multi-Objective Evolutionary Algorithm (MMOEA) is ...
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03/16/2022
Adaptive Objective Configuration in Bi-Objective Evolutionary Optimization for Cervical Cancer Brachytherapy Treatment Planning
The Multi-Objective Real-Valued Gene-pool Optimal Mixing Evolutionary Al...
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03/11/2022
Solving Multi-Structured Problems by Introducing Linkage Kernels into GOMEA
Model-Based Evolutionary Algorithms (MBEAs) can be highly scalable by vi...
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03/08/2022
Evolutionary Neural Cascade Search across Supernetworks
To achieve excellent performance with modern neural networks, having the...
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03/01/2022
On genetic programming representations and fitness functions for interpretable dimensionality reduction
Dimensionality reduction (DR) is an important technique for data explora...
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02/24/2022
Data variation-aware medical image segmentation
Deep learning algorithms have become the golden standard for segmentatio...
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02/23/2022
Mixed-Block Neural Architecture Search for Medical Image Segmentation
Deep Neural Networks (DNNs) have the potential for making various clinic...
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02/22/2022
Multi-Objective Dual Simplex-Mesh Based Deformable Image Registration for 3D Medical Images – Proof of Concept
Reliably and physically accurately transferring information between imag...
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02/14/2022
Evolvability Degeneration in Multi-Objective Genetic Programming for Symbolic Regression
Genetic programming (GP) is one of the best approaches today to discover...
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02/10/2022
Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning
Emotion recognition in children can help the early identification of, an...
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02/04/2022
Heed the Noise in Performance Evaluations in Neural Architecture Search
Neural Architecture Search (NAS) has recently become a topic of great in...
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09/06/2021
Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration
Deformable Image Registration (DIR) can benefit from additional guidance...
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04/16/2021
A Novel Surrogate-assisted Evolutionary Algorithm Applied to Partition-based Ensemble Learning
We propose a novel surrogate-assisted Evolutionary Algorithm for solving...
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02/08/2021
Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization
Real-world problems are often multi-objective with decision-makers unabl...
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01/23/2020
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms
There has recently been great progress in automatic segmentation of medi...
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01/21/2020
An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical Images
Anatomical landmark correspondences in medical images can provide additi...
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09/09/2019
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms
Machine Learning (ML) is proving extremely beneficial in many healthcare...
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07/04/2019
On Explaining Machine Learning Models by Evolving Crucial and Compact Features
Feature construction can substantially improve the accuracy of Machine L...
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04/03/2019
A Model-based Genetic Programming Approach for Symbolic Regression of Small Expressions
The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) is a model-b...
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04/03/2019