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INFORMS-QSR and ENBIS Webinar Series Presents: Prof. Raed Al Kontar, University of Michigan, Speaks on The Modern Gaussian Process
I present some of our group’s recent work on Gaussian processes (GP) both from a theoretical and applied perspective. I first introduce the Renye GP which is an alternative objective for GPs capable of improving generalization through tuning the induced regularization. I then highlight the ability of mini-batch stochastic gradient descent to perform inference in GPs (a correlated setting) and hence scaling them far beyond what has been thought possible. From an applied perspective, I introduce predictive GP models that can be used for joint event data, weakly supervised settings and state of the art multi-output regression.

May 7, 2021 10:00 AM in Eastern Time (US and Canada)

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Raed Al Kontar
Assistant Professor in the Department of Industrial & Operations Engineering @University of Michigan
His main research interest is data science using probabilistic models. He aims to understand the foundations of such models in extracting interpretable knowledge and generalizing to new data. Raed also focuses on data science applications within Internet of Things (IoT) enabled systems, specifically in tele-service settings.