Zhe’s PhD Defense - Toward Out-Of-Distribution Generalization Of Deep Learning Models
Ph.D. Dissertation Defense by Zhe Wang, Tues., 04/02/24, at 12:00PM (ET) Committee:
Generalization refers to how a machine model adapts properly to new, previously unseen data. We focus on OOD (out of distribution) generalization.
Deep learning constructs networks of parameterized functional modules and is trained from reference examples using gradient-based optimization [Lecun19].
Since it is hard to estimate gradients through functions of discrete random variables, researching on how to make deep learning behave well on discrete structured data and structured representation interests us. Developing such techniques are an active research area. We focus on investigating interpretable and scalable techniques for doing so.
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Thanks for reading!
Ph.D. Dissertation Defense by Zhe Wang, Tues., 04/02/24, at 12:00PM (ET) Committee:
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