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The Quarks of Attention

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  • UserProfessor Pierre Baldi - Distinguished Professor, Department of Computer Science Director, Institute for Genomics and Bioinformatics Associate Director, Center for Machine Learning and Intelligent Systems, University of California, Irvine
  • ClockWednesday 26 January 2022, 15:05-15:55
  • HouseOnline.

If you have a question about this talk, please contact Ben Karniely.

Attention plays a fundamental role in both natural and artificial intelligence systems. In deep learning, several attention-based neural network architectures have been proposed to tackle problems in natural language processing (NLP) and beyond, including transformer architectures which currently achieve state-of-the-art performance in NLP tasks. In this presentation we will: 1) identify and classify the most fundamental building blocks (quarks) of attention, both within and beyond the standard model of deep learning; 2) identify how these building blocks are used in all current attention-based architectures, including transformers; 3) demonstrate how transformers can effectively be applied to new problems in physics, from particle physics to astronomy; and 4) present a mathematical theory of attention capacity where, paradoxically, one of the main tools in the proofs is itself an attention mechanism.

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This talk is part of the Wednesday Seminars - Department of Computer Science and Technology series.

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