Search Results for author: Masanori Hashimoto

Found 2 papers, 2 papers with code

Hidden-Fold Networks: Random Recurrent Residuals Using Sparse Supermasks

1 code implementation24 Nov 2021 Ángel López García-Arias, Masanori Hashimoto, Masato Motomura, Jaehoon Yu

Deep neural networks (DNNs) are so over-parametrized that recent research has found them to already contain a subnetwork with high accuracy at their randomly initialized state.

When Single Event Upset Meets Deep Neural Networks: Observations, Explorations, and Remedies

1 code implementation10 Sep 2019 Zheyu Yan, Yiyu Shi, Wang Liao, Masanori Hashimoto, Xichuan Zhou, Cheng Zhuo

We are then able to analytically explore the weakness of a network and summarize the key findings for the impact of SIPP on different types of bits in a floating point parameter, layer-wise robustness within the same network and impact of network depth.

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