Special session on machine learning for test and diagnosis

The special session focuses on using Machine Learning (ML) techniques on different applications in test and diagnosis. The first contribution discusses how to close the gap between working silicon and a working system by using ML. The second presentation then talks an alternative ML view and its various applications such as functional verification, Fmax prediction, and production yield optimization. The last presentation discusses using supervised ML on volume diagnosis to further improve the accuracy of identifying root causes.