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Calibrating Process Variation at System Level with In-Situ Low-Precision Transfer Learning for Analog Neural Network Processors.

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Title: Calibrating Process Variation at System Level with In-Situ Low-Precision Transfer Learning for Analog Neural Network Processors.
Authors: Kaige Jia1, Zheyu Liu1, Qi Wei1, Fei Qiao1, qiaofei@tsinghua.edu.cn, Xinjun Liu2, Yi Yang1, Hua Fan3, Huazhong Yang1
Source: DAC: Annual ACM/IEEE Design Automation Conference; 2018, Issue 55, p193-198, 6p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 155539247
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PubType: Conference
PubTypeId: conference
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  Data: Calibrating Process Variation at System Level with In-Situ Low-Precision Transfer Learning for Analog Neural Network Processors.
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  Data: <searchLink fieldCode="JN" term="%22DAC%3A+Annual+ACM%2FIEEE+Design+Automation+Conference%22">DAC: Annual ACM/IEEE Design Automation Conference</searchLink>; 2018, Issue 55, p193-198, 6p
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      – Type: doi
        Value: 10.1145/3195970.3196004
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      – Code: eng
        Text: English
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        PageCount: 6
        StartPage: 193
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      – TitleFull: Calibrating Process Variation at System Level with In-Situ Low-Precision Transfer Learning for Analog Neural Network Processors.
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            NameFull: Kaige Jia
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            NameFull: Zheyu Liu
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            NameFull: Xinjun Liu
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            NameFull: Yi Yang
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            NameFull: Hua Fan
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            NameFull: Huazhong Yang
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            – D: 01
              M: 01
              Text: 2018
              Type: published
              Y: 2018
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              Value: 55
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            – TitleFull: DAC: Annual ACM/IEEE Design Automation Conference
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