Found 2 essays matching the above criteria.
1. Evaluating Unsupervised Methods for Out-of-Distribution Detection on Semantically Similar Image DataUniversity essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)
Abstract : Out-of-distribution detection considers methods used to detect data that deviates from the underlying data distribution used to train some machine learning model. This is an important topic, as artificial neural networks have previously been shown to be capable of producing arbitrarily confident predictions, even for anomalous samples that deviate from the training distribution. READ MORE
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)
Abstract : Meta-learning is an approach to machine learning that teaches models how to learn new tasks with only a handful of examples. However, meta-learning requires a large labeled dataset during its initial meta-learning phase, which restricts what domains meta-learning can be used in. READ MORE