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Vos, Daniël (author)
In the present day we use machine learning for sensitive tasks that require models to be both understandable and robust. Although traditional models such as decision trees are understandable, they suffer from adversarial attacks. When a decision tree is used to differentiate between a user's benign and malicious behavior, an adversarial attack...
master thesis 2020
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Naseri Jahfari, Arman (author)
Rainfall is increasing in frequency and intensity due to climate change. Hydrological models exist that can report bottlenecks in urban infrastructures. However, these require accurate rainfall estimations with high temporal and spatial resolution. The fulfillment of these requirements is challenged due to high costs. This can be solved with...
master thesis 2019
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Anand, Kanav (author)
Deep learning is proving to be a useful tool in solving problems from various domains. Despite a rich research activity leading to numerous interesting deep learning models, recent large scale studies have shown that with hyperparameter optimization it is hard to distinguish these models based on their final performance. Hyperparameter...
master thesis 2019
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Radojević, Jovana (author)
A lot of attention has recently been focused on possible benefits of the cooperation between machines and humans. Taking the best from machines and humans and joining them together can produce results which exceed each collaborating partner performing separately. A common belief is that the<br/>key for good cooperation is an excellent...
master thesis 2017
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