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Open access Sep 2026

A novel approach to lossless convolutional neural network compression via progressive knowledge distillation-incorporated low-rank compression.

Model compression is widely used to deploy large neural networks on resource-constrained edge devices. Among existing techniques, low-rank composition is theoretically grounded in approximation theory and provides a strong basis for preserving model performance after compression. However, in practice, even state-of-the...

Ya-Ping He, Hao Wu, Wei-Bo Liu et al. · 0 citations

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