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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 April 30, Ismail Ben Ayed (Associate Professor at Ecole de Technologie Superieure (ETS) Montreal (Université du Québec)) presented "Few-Shot Learning: Are We Making Progress?”
Despite their unprecedented performances when trained on large-scale labeled data, deep-learning models are seriously challenged when dealing with unseen classes and limited labeled instances. This talk discusses recent developments in the subject of learning with limited labels, leveraging unlabeled data with structural priors, and connecting them under a unifying information-theoretic perspective.
Watch the full presentation below:
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