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Department of Computing Science faculty candidate Dr. Wenbin Zhang, postdoctoral associate, Carnegie Mellon University, will present a virtual lecture on Thursday, March 31, at 1:00 p.m. via Zoom online meeting. Zhang’s research investigates the theoretical foundations of machine learning with a focus on societal impact and welfare.
Talk Title: Fairness and Graph Deep Generation through the Lens of Time
Talk Abstract: Many problems in machine learning are time-dependent in nature, which brings unique and complicated challenges such as uncertainty on the event of interest and the mutual interactions among static and dynamic patterns. To overcome these challenges, devising new techniques becomes essential. In this talk, I will be showing some of these new techniques through some machine learning problems I have recently worked on, such as fairness under uncertainty to support social fairness, and a generic framework of factorized deep generative models for interpretable dynamic graph generation, which provide necessary complements to these important yet challenging tasks.
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