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학술대회 CP-decomposition with Tensor Power Method for Convolutional Neural Networks Compression
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저자
마셀라, 이승익
발행일
201702
출처
International Conference on Big Data and Smart Computing (BigComp) 2017, pp.115-118
DOI
https://dx.doi.org/10.1109/BIGCOMP.2017.7881725
협약과제
16MS5200, 사용자 디지털 감성 DNA에 기반한 디지털생명체 기술 개발, 이승익
초록
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-of-the-art previous work with no more accuracy loss.
KSP 제안 키워드
Accuracy loss, Complex image, Compression method, Computation cost, Convolution neural network(CNN), Image classification, Power Method, Smart Phone, Smart devices, computational cost, fine-tuning