AI Seminar Series 2022: Tyler Hayes

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 May 20, 2022, Tyler Hayes from the Rochester Institute of Technology presented "Efficient Lifelong Machine Learning in Deep Neural Networks" at the AI Seminar.

Humans continually learn and adapt to new knowledge and environments throughout their lifetimes. Rarely does learning new information cause humans to catastrophically forget previous knowledge. While deep neural networks (DNNs) now rival human performance on several supervised machine perception tasks, when updated on changing data distributions, they catastrophically forget previous knowledge. Enabling DNNs to learn new information over time opens the door for new applications such as self-driving cars that adapt to seasonal changes or smartphones that adapt to changing user preferences. In this talk, we propose new methods and experimental paradigms for efficiently training continual DNNs without forgetting. We then apply these methods to several visual perception tasks.

Watch the full presentation below:

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