Position: Addressing small labeled data in machine learning training
Supervising team: Mária Bieliková (KInIT), Ivan Srba (KInIT)
To circumvent the issue, many approaches are emerging and are presently researched by many researchers: meta-learning, transfer-learning, weak-supervision, zero/one-shot learning, semi-supervised learning. Each of these fields (or combination thereof) presents opportunities for new discoveries. Orthogonal to this, explainability and interpretability of models is an important factor to consider and advances in this regard are welcome (generally in AI and particularly in the mentioned approaches).