123 citations · 282 across the 44 of their papers we have counts for
4 papers · 1 filter
Shrink-Perturb Improves Architecture Mixing during Population Based Training for Neural Architecture Search
Alexander Chebykin, Arkadiy Dushatskiy, Tanja Alderliesten +1
In this work, we show that simultaneously training and mixing neural networks is a promising way to conduct Neural Architecture Search (NAS). For hyperparameter optimization, reusi…
Multi-Objective Population Based Training
Arkadiy Dushatskiy, Alexander Chebykin, Tanja Alderliesten +1
Population Based Training (PBT) is an efficient hyperparameter optimization algorithm. PBT is a single-objective algorithm, but many real-world hyperparameter optimization problems…
Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization
Timo M. Deist, Monika Grewal, Frank J. W. M. Dankers +2
Real-world problems are often multi-objective with decision-makers unable to specify a priori which trade-off between the conflicting objectives is preferable. Intuitively, buildin…
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms
Marco Virgolin, Ziyuan Wang, Tanja Alderliesten +1
Machine Learning (ML) is proving extremely beneficial in many healthcare applications. In pediatric oncology, retrospective studies that investigate the relationship between treatm…