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Abstract
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Unlike any other method, deep learning has come as a forceful wave that knocked many of us to the sand, regardless of which direction we stood before. In this talk, I will begin with a brief introduction of the main steps of deep learning algorithm, and then use it to reflect on some of the statistical methods that I have developed over the past two decades, specifically classification trees for multiple binary responses (CTMBR) and multivariate adaptive splines for longitudinal data analysis (MASAL). I will discuss the pros and cons of these methods, and offer my own perspective in our missed opportunities as well as new challenges and opportunities.
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