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Tuesday, June 5 • 2:15pm - 3:00pm
Your Attention, Please! Building Intuition Around Attention-based Text Classification Models

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While neural networks are now established as state-of-the-art tools in nearly every NLP task, they are also complex. Interpretability of NN predictions remains elusive. In applications involving text data, this is can be problematic, especially if stakeholders prioritize transparency in machine learning. In this talk, we review a NN architecture, called the Hierarchical Attention Network (Yang et al. 2015) that takes a step in the direction of interpretability. We develop intuition for the model architecture and present its relative strengths and weaknesses. By learning to pay attention to the most important parts of a document--in a data-driven way--we can understand explicitly which text drives a particular prediction.

avatar for Andy Kreek

Andy Kreek

Data Scientist, Allstate

Tuesday June 5, 2018 2:15pm - 3:00pm
P1808 Normandale Partnership Center, 9700 France Ave So, Bloomington, MN 55431