Abstract Convolutional neural networks (CNNs) have shown good performance in many practical applications. However, their high computational and storage requirements make them difficult to deploy on resource-constrained devices. To address this issue, paper, we propose a novel iterative structured pruning algorithm for CNNs based the recursive least squares (RLS) optimization. Our combines inver...