Schmidt’s work focuses on the development of substantially faster methods to deal with hyper-parameters. The key innovation of his work is adapting hyper-parameters at the same time as the model is learning from data.
My primary research area is machine learning, where the goal is to understand and develop algorithms that improve prediction and decision-making capabilities with experience.
Being a Killam laureate was an honour that tells me my hard work is paying off and being acknowledged, and that I am on the right track.
