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9 March 2021, Machine learning, logic, and structured knowledge, Balder ten Cate

Speaker: Balder ten Cate (Google Research)
Date: Tuesday 9 March 2021
Time: 18:15-19:00
Location: Online via Zoom

Over the last decade, advances in machine learning have taken the computer science community by storm, enabling new applications and pushing the envelope on existing ones. Even on tasks that are traditionally viewed as falling in the domain of logical reasoning (e.g., reading comprehension tasks), deep neural models are now the state-of-the-art. Furthermore, logic and learning are perceived by some as being distinct or even opposing approaches. At the same time, while various algorithmic and hardware limitations that inhibited deep learning solutions in the past have been successfully addressed, other fundamental problems arise, such as problems concerning fairness, explainability, and controllability. In this talk, I will discuss a few problems at the intersection of machine learning and logic, including providing deep models with means to access structured knowledge.

Zoom link: https://uva-live.zoom.us/j/82670894282

For more information, see https://research.google/people/107268/.

Please note that this newsitem has been archived, and may contain outdated information or links.