Tensor Regression Networks with various Low-Rank Tensor Approximations

doi:doi:10.57702/udi4c0ow

Tensor Regression Networks with various Low-Rank Tensor Approximations

Tensor regression networks achieve high compression rate of neural networks while having slight impact on performances. They do so by imposing low tensor rank structure on the weight matrices of fully connected layers.

Data and Resources

Original MetadataJSON
The json representation of the dataset with its distributions based on DCAT.
Explore
- Preview
- Download

Cite this as

Xingwei Cao, Guillaume Rabusseau (2024). Dataset: Tensor Regression Networks with various Low-Rank Tensor Approximations. https://doi.org/10.57702/udi4c0ow

DOI retrieved: December 2, 2024

Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Xingwei Cao
More Authors	Guillaume Rabusseau