Abstract: Low resource applications in machine learning deal with limited data, which are usually resolved with either model regularization or clever data augmentation techniques. In this preliminary work, I will discuss and showcase utilizing difference data can improve the performance of several different models that hopelessly overfit otherwise. Hoping for a discussion about possible reasoning behind these results.
Posted by: Alessandro Ferrero