Yisong Yue, Assistant Professor of Computing and Mathematical Sciences, is a recipient of the Bloomberg Data Science Research Grant Program. The program aims to support cutting-edge research in the broad field of machine learning, including specific areas such as natural language processing, information retrieval, machine-translation and deep neural networks. Professor Yue has proposed to study an alternative notion of interpretability, which he calls “dynamic interpretability”. The goal of dynamically interpretable models is to make predictions that are interpretable, rather than have the model itself be explicitly interpretable. With this alternative goal, one can circumvent much of the inherent tension between accuracy and traditional “static” interpretability, and move one step closer to interpretable production-strength models.[Bloomberg release]
Professor Yue Receives Bloomberg Data Science Grant
June 13, 2016