Spring 2017

Machine Teaching in Interactive Learning

Monday, Feb. 13, 2017 10:45 am11:30 am PST

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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.