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MODEL COMPRESSION BY SPARSITY-INDUCING REGULARIZATION OPTIMIZATION
MODEL COMPRESSION BY SPARSITY-INDUCING REGULARIZATION OPTIMIZATION
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机译:模型压缩通过稀疏诱导正则化优化
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摘要
The performance of a neural network (NN) and/or deep neural network (DNN) can limited by the number of operations being performed as well as management of data among the various memory components of the NN/DNN. A sparsity-inducing regularization optimization process is performed on a machine learning model to generate a compressed machine learning model. A machine learning model is trained using a first set of training data. A sparsity-inducing regularization optimization process is executed on the machine learning model. Based on the sparsity-inducing regularization optimization process, a compressed machine learning model is received. The compressed machine learning model is executed to generate one or more outputs.
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