Abstract-Convolutional Neural Networks (CNNs) has shown a great success in many areas including complex image classification tasks. However, they need a lot of memory and computational cost, which hinders them from running in relatively low-end smart devices such as smart phones. We propose a CNN compression method based on CP-decomposition and Tensor Power Method. We also propose an iterative fine tuning, with which we fine-tune the whole network after decomposing each layer, but before decomposing the next layer. Significant reduction in memory and computation cost is achieved compared to state-ofthe-art previous work with no more accuracy loss.
Astrid et al. in REF proposed a CNN compression method based on CPD and the tensor power method where they achieved significant reduction in memory and computational cost.
CP-decomposition with Tensor Power Method for Convolutional Neural Networks compression
2017 IEEE International Conference on Big Data and Smart Computing (BigComp)
2017 IEEE International Conference on Big Data and Smart Computing (BigComp)
Mathematics Computer Science