Learn about the concept of effective attention in deep learning through a 36-minute lecture that progresses from a foundational self-attention recap to advanced topics in attention mechanisms. Explore the mathematical and practical aspects of effective attention, followed by norm-based analysis techniques for understanding attention patterns. Gain insights into related research and alternative approaches in the field, making this lecture valuable for both newcomers to attention mechanisms and experienced practitioners seeking deeper understanding.
Pairwise Feature Importance and Effective Attention in Self-Attention Networks
Overview
Syllabus
Course checkpoint
Self-attention recap
Effective attention
Norm-based analysis
Other works
Taught by
UofU Data Science
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