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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.

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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

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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