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The AI Seminar is a weekly meeting at the University of Alberta where researchers interested in artificial intelligence (AI) can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics can be related in any way to artificial intelligence, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.
On December 4, 2020, professor at Duke University Cynthia Rudin presented “Simpler Models Exist and How Can We Find Them?”.
Complex hypothesis spaces are not always necessary or helpful for many domains. In particular, models and their predictions are often made easier to understand by adding interpretability constraints, which shrink the hypothesis space -- that is, they make the model simpler. However, adding extra constraints can make optimization (exponentially) harder. In this talk, Cynthia asks: Can we show that a simple-but-accurate machine learning model might exist for our problem, before actually finding it?
Watch the full presentation below:
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