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Imani et al., 2018 - Google Patents

Deep neural network acceleration framework under hardware uncertainty

Imani et al., 2018

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Document ID
17024748287629423617
Author
Imani M
Wang P
Rosing T
Publication year
Publication venue
2018 19th International Symposium on Quality Electronic Design (ISQED)

External Links

Snippet

Deep Neural Networks (DNNs) are known as effective model to perform cognitive tasks. However, DNNs are computationally expensive in both train and inference modes as they require the precision of floating point operations. Although, several prior work proposed …
Continue reading at www.isqed.org (PDF) (other versions)

Classifications

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    • G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
    • G—PHYSICS
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    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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