Date of Award
Master of Science
Neural networks can be repurposed via reprogramming to perform new tasks, which are different from the tasks they were originally trained for. We introduce new and improved reprogramming technique that, compared to prior works, achieves better accuracy, scalability, and can be successfully applied to more complex tasks. While prior literature focuses on potential malicious uses of reprogramming, we argue that reprogramming can be viewed as an efficient training method. Our reprogramming method allows for re-using existing pre-trained models and easily reprogramming them to perform new tasks. This technique requires a lot less effort and hyperparameter tuning compared training new models from scratch. Therefore, we believe that our improved and scalable reprogramming method has potential to become a new method for creating machine learning models.
Kloberdanz, Eliska, "Reprogramming of neural networks: A new and improved machine learning technique" (2020). Graduate Theses and Dissertations. 17943.