Tutorial
Power-efficient neural networks using low-precision data types and quantization
Thomas Pfeil
205 B
Abstract:
As neural networks grow, sustainability and cost become major challenges. This tutorial covers low-precision data types, quantization methods, and hands-on applications. Attendees will gain tools to maintain model performance while optimizing for efficiency on edge and large-scale deployments.
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