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Attention Networks for Natural Language Processing


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Neural-network-based methods for natural language processing (NLP) constitute an area of significant recent technical progress, with many interesting real-world applications. The Transformer Network is one of the newest and most powerful approaches of this type. This algorithm is based on repeated application of attention networks, in an encoder-decoder framework. In this presentation the basics of all-attention models (the Transformer) for NLP will be described, with application in areas like text synthesis (e.g., suggesting email text) and language translation.

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Status Archived
Date Thursday, March 26th, 2020
Time 4:30pm - 6:30pm
Location Virtual Classroom
Leader Lawrence Carin
Enrolled 114