Talks
Spring 2017
Machine Teaching in Interactive Learning
Monday, February 13th, 2017, 10:45 am–11:30 am
Event:
Location:
Calvin Lab Auditorium
If machine learning is to discover knowledge from data, then machine teaching is an inverse problem to pass the knowledge on. More precisely, given a learning algorithm and a target model, the goal of machine teaching is to construct an optimal (e.g. the smallest) training set from which the algorithm will learn the target model. I will discuss several aspects of machine teaching that connect to interactive machine learning.
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