Rank Selection of CP-decomposed Convolutional Layers with Variational Bayesian Matrix Factorization

Understand

Convolutional Neural Networks (CNNs) is one of successful method in many areas such as image classification tasks.

• However, the amount of memory and computational cost needed for CNNs inference obstructs them to run efficiently in mobile devices because of memory and computational ability limitation.
• One of the method to compress CNNs is compressing the layers iteratively, i.e.
• by layer-by-layer compression and fine-tuning, with CP-decomposition in convolutional layers.