Convolutional Deep Learning Networks.pdf

1511.06530.pdf
Preview of convolutional deep learning networks
🔗 Source: arxiv.org
📊 Size: 1022 KB
📄 Pages: 16 pages
⬇️ Downloads: 91

Summary

Researchers from Samsung Electronics and Seoul National University proposed a simple and effective scheme to compress deep convolutional neural networks (CNNs) for fast and low-power mobile applications, called one-shot whole network compression. The scheme consists of three steps: rank selection with variational Bayesian matrix factorization, Tucker decomposition on kernel tensor, and fine-tuning to recover accumulated loss of accuracy. The proposed scheme was tested on various CNNs (AlexNet, VGG-S, GoogLeNet, and VGG-16) and achieved significant reductions in model size, runtime, and energy consumption with a small loss in accuracy.

Description

Researchers from Samsung Electronics and Seoul National University proposed a simple and effective scheme to compress deep convolutional neural networks (CNNs)...

Technical Information

  • File Format: PDF
  • File Size: 1022 KB
  • Pages: 16
  • Language: EN
  • Total Downloads: 91
  • Last Updated: 2 hours ago

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This PDF document about convolutional deep learning networks provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into convolutional deep learning networks.

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