CORDIS Project
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This project aims to develop machine learning algorithms capable of deep transfer learning, allowing models to generalize knowledge across different domains. It addresses the challenge of limited data availability by enabling algorithms to discern structural patterns applicable to various tasks.
Machine learning's goal is to devise algorithms that improve with experience.
Currently, experience is largely defined to be the amount of available data.
Unfortunately, acquiring data can be time consuming (e.g., annotating documents), monetarily expensive (e.g., genetic testing), physically invasive (e.g., collecting a tissue sample) or unavailable in sufficient quantities (e.g., data about rarediseases).
For some tasks, this makes it challenging to obtain the quantities of data necessary to…
KATHOLIEKE UNIVERSITEIT LEUVEN
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