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Neural Network Compression: Difference between revisions
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* Mozer and Smolensky (1988)<ref name="mozer1988skeletonization"></ref> use a gate for each neuron. Then the sensitivity and be estimated with the derivative w.r.t the gate. | * Mozer and Smolensky (1988)<ref name="mozer1988skeletonization"></ref> use a gate for each neuron. Then the sensitivity and be estimated with the derivative w.r.t the gate. | ||
* Karnin estimates the sensitivity by monitoring the change in weight during training. | * Karnin <ref name="karnin1990simple"></ref> estimates the sensitivity by monitoring the change in weight during training. | ||
==Factorization== | ==Factorization== | ||
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{{reflist|refs= | {{reflist|refs= | ||
<ref name="mozer1988skeletonization">Mozer, M. C., & Smolensky, P. (1988). Skeletonization: A technique for trimming the fat from a network via relevance assessment. (NeurIPS 1988). [https://proceedings.neurips.cc/paper/1988/file/07e1cd7dca89a1678042477183b7ac3f-Paper.pdf PDF]</ref> | <ref name="mozer1988skeletonization">Mozer, M. C., & Smolensky, P. (1988). Skeletonization: A technique for trimming the fat from a network via relevance assessment. (NeurIPS 1988). [https://proceedings.neurips.cc/paper/1988/file/07e1cd7dca89a1678042477183b7ac3f-Paper.pdf PDF]</ref> | ||
<ref name="karnin1990simple">Karnin, E. D. (1990). A simple procedure for pruning back-propagation trained neural networks. (IEEE TNNLS 1990). [https://ieeexplore.ieee.org/document/80236 IEEE Xplore]</ref> | |||
}} | }} | ||