Transformational machine learning (TMA) is a new approach to machine learning (ML). The method is based on human learning - it learns from multiple problems and improves performance while it learns.
Ross D King is Professor of Machine Intelligence at Chalmers and was recruited by WASP in 2019 as a Wallenberg Chair in AI. The method developed by him and his colleagues could accelerate the identification and production of new drugs by improving the machine learning systems which are used to identify them. The results are recently published in PNAS.
"A typical ML system has to start from scratch when learning to identify a new type of drug, dealing with a single issue at a time. A typical ML approach will search for drug molecules of a particular shape, for example. TML instead uses the connection of the drugs to other drug discovery problems. This makes TML a much more powerful approach," says Ross D King.
Read the news text from WASP: A Machine that Learns How to Learn - 'Transformational' approach to machine learning could accelerate search for new disease treatments
Read the study in PNAS: Transformational machine learning: Learning how to learn from many related scientific problems
