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Alternating optimization method based on nonnegative matrix factorizations for deep neural networks

The proposed method uses the MNIST and CIFAR10 datasets for fully-connected DNNs.

Data and Resources

Cite this as

Tetsuya Sakurai, Akira Imakura, Yuto Inoue, Yasunori Futamura (2024). Dataset: Alternating optimization method based on nonnegative matrix factorizations for deep neural networks. https://doi.org/10.57702/b7623jfz

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.1605.04639
Author Tetsuya Sakurai
More Authors
Akira Imakura
Yuto Inoue
Yasunori Futamura
Homepage https://arxiv.org/abs/1806.07733