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Apr 30, 2019 · Artificial Intelligence
How Can Deep Neural Networks Be Accelerated and Compressed? Key Techniques Explained
This article reviews why deep neural networks are over‑parameterized, outlines the challenges of deploying them on mobile and embedded devices, and presents six major strategies—pruning, low‑rank approximation, filter selection, quantization, knowledge distillation, and novel architecture design—to accelerate and compress models while preserving performance.
Knowledge DistillationQuantizationdeep learning
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