Event
Siamak Ravanbakhsh (McGill - Computer Science)
Friday, September 20, 2019 15:30to16:30
Burnside Hall
Room 1205, 805 rue Sherbrooke Ouest, Montreal, QC, H3A 0B9, CA
Abstract:
Symmetry has played a significant role in modern physics, in part by constraining the physical laws. I will discuss how it could play a fundamental role in AI by constraining the deep model design. In particular, I focus on discrete domain symmetries and through examples show how we can use this inductive bias as a principled means for constraining a feedforward layer and significantly improving its sample efficiency.
Speaker
Siamak Ravanbakhsh is an Assistant Professor, School of Computer Science, Ï㽶ÊÓƵ. His research interests include inference within structured, complex and combinatorial domains using graphical and structured deep models.
Seminar website:
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