NIST · ИТ · 4faa7add46164a5e7d6d
Streaming Batch Gradient Tracking for Neural Network Training
Faster and more energy efficient hardware accelerators are critical for machine learning on very large datasets. The energy cost of performing vector-matrix multiplication and repeatedly moving neural network models in and out of memory motivates a search
NIST · ИТОфициальный источник · 2020-04-03
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"title_en": "Streaming Batch Gradient Tracking for Neural Network Training",
"designation": "",
"series": "",
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"date": "2020-04-03",
"date_original": "April 3, 2020",
"url": "https://www.nist.gov/publications/streaming-batch-gradient-tracking-neural-network-training",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Siyuan Huang , Brian D. Hoskins , Matthew W. Daniels , Mark D. Stiles , Gina C. Adam",
"abstract_excerpt_en": "Faster and more energy efficient hardware accelerators are critical for machine learning on very large datasets. The energy cost of performing vector-matrix multiplication and repeatedly moving neural network models in and out of memory motivates a search",
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{
"title_en": "Streaming Batch Gradient Tracking for Neural Network Training",
"designation": "",
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"date": "2020-04-03",
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"url": "https://www.nist.gov/publications/streaming-batch-gradient-tracking-neural-network-training",
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"authors_en": "Siyuan Huang , Brian D. Hoskins , Matthew W. Daniels , Mark D. Stiles , Gina C. Adam",
"abstract_excerpt_en": "Faster and more energy efficient hardware accelerators are critical for machine learning on very large datasets. The energy cost of performing vector-matrix multiplication and repeatedly moving neural network models in and out of memory motivates a search"
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