Low-Rank Factorization
The key idea behind low-rank factorization is to replace high-dimensional tensors with lower-dimensional tensors. One type of low-rank factorization is compact convolutional filters, where the over-parameterized (having too many parameters) convolution filters are replaced with compactblocks to both reduce the number of parameters and increase speed.