Your... Machine learning offers techniques with immense modeling power. There is, however, no general scheme for optimizing a machine learning algorithm. Namely, the optimum hyperparameter settings depend on the dataset, upon...
Machine learning offers techniques with immense modeling power. There is, however, no general scheme for optimizing a machine learning algorithm. Namely, the optimum hyperparameter settings depend on the dataset, upon which models are to be trained. A, more or less recent, topic called meta machine learning attempts to optimize certain machine learning algorithms using, e.g., reinforcement learning. Drawing inspiration from this topic, this thesis aims to investigate the possibility to implement a reward-based algorithm for optimization of a neural network’s hyperparameter settings.
Suggested Work-plan:
Pre-requisites: Programming, linear algebra and a familiarity with reading scientific articles. Prior knowledge about machine learning is preferrable but not required.
This work can be done by 1-2 students. Different takes on the thesis include the optimisation of: dense networks, and; convolutional networks
At Saab, we constantly look ahead and push boundaries for what is considered technically possible. We collaborate with colleagues around the world who all share our challenge – to make the world a safer place.
20-03-2024
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