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Keynote & Tutorial – Continual Learning and Catastrophic Forgetting

2024.ccneuro.org · 481 words · saved by 1 readers

Continual learning is a key aspect of intelligence. The human brain is able to incrementally learn new skills without compromising those that were learned before, as well as to integrate and contrast new information with earlier acquired knowledge. Intriguingly, deep neural networks, although rivaling human intelligence in other ways, almost completely lack this ability to learn continually. Most strikingly, when these networks learn something new, they tend to “catastrophically” forget what was learned before. In recent years, continual learning has become a hot topic in deep learning, and it is considered one of the main open challenges in the field. In this keynote and tutorial, we will provide an overview of the deep learning research on continual learning of the past years. We will do so with a focus on the insights and intuitions that this line of research has generated with regards to the computational principles of continual learning. We hope that these insights will inform and

Keynote & Tutorial – Continual Learning and Catastrophic Forgetting Skip to main content Keynote & Tutorial Wednesday, August 7, 3:20 - 4:00 pm, Kresge Hall (Keynote) Wednesday, August 7, 4:30 - 6:15 pm, Little Kresge (Tutorial) Continual Learning and Catastrophic Forgetting Gido van de Ven 1 , Dhireesha Kudithipudi 2 , 1 KU Leuven, 2 The University of Texas at San Antonio. Continual learning is a key aspect of intelligence. The human brain is able to incrementally learn new skills without compromising those that were learned before, as well as to integrate and contrast new information w

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