Searched for: author%3A%22Dushatskiy%2C+A.%22
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Dushatskiy, A. (author)
Recently great achievements have been obtained with Artificial Intelligence (AI) methods including human-level performance in such challenging areas as image processing, natural language processing, computational biology, and game playing. Arguably, one of the most societally important application fields of such methods is healthcare. <br/>AI is...
doctoral thesis 2023
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Chebykin, Alexander (author), Dushatskiy, A. (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
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, reusing the partially trained weights allows for efficient search, as was previously demonstrated by the Population Based Training (PBT) algorithm. We propose PBT-NAS,...
conference paper 2023
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Dushatskiy, A. (author), Lowe, Gerry (author), Bosman, P.A.N. (author), Alderliesten, T. (author)
Deep learning algorithms have become the golden standard for segmentation of medical imaging data. In most works, the variability and heterogeneity of real clinical data is acknowledged to still be a problem. One way to automatically overcome this is to capture and exploit this variation explicitly. Here, we propose an approach that improves...
conference paper 2022
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Bosma, Martijn M.A. (author), Dushatskiy, A. (author), Grewal, M. (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
Deep Neural Networks (DNNs) have the potential for making various clinical procedures more time-efficient by automating medical image segmentation. Due to their strong, in some cases human-level, performance, they have become the standard approach in this field. The design of the best possible medical image segmentation DNNs, however, is task...
conference paper 2022
document
Dushatskiy, A. (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
Neural Architecture Search (NAS) has recently become a topic of great interest. However, there is a potentially impactful issue within NAS that remains largely unrecognized: noise. Due to stochastic factors in neural network initialization, training, and the chosen train/validation dataset split, the performance evaluation of a neural network...
conference paper 2022
document
Dushatskiy, A. (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
We propose a novel surrogate-assisted Evolutionary Algorithm for solving expensive combinatorial optimization problems. We integrate a surrogate model, which is used for fitness value estimation, into a state-of-the-art P3-like variant of the Gene-Pool Optimal Mixing Algorithm (GOMEA) and adapt the resulting algorithm for solving non-binary...
conference paper 2021
Searched for: author%3A%22Dushatskiy%2C+A.%22
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