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Accelerating Deep Learning by Focusing on the Biggest Losers
This paper introduces Selective-Backprop, a technique that accelerates t...
10/02/2019 ∙ by Angela H. Jiang, et al. ∙
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The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design
The past decade has seen a remarkable series of advances in machine lear...
11/13/2019 ∙ by Jeffrey Dean, et al. ∙
92
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Distributed Representations of Words and Phrases and their Compositionality
The recently introduced continuous Skip-gram model is an efficient metho...
10/16/2013 ∙ by Tomas Mikolov, et al. ∙
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TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
TensorFlow is an interface for expressing machine learning algorithms, a...
03/14/2016 ∙ by Martín Abadi, et al. ∙
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Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Neural Machine Translation (NMT) is an end-to-end learning approach for ...
09/26/2016 ∙ by Yonghui Wu, et al. ∙
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Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
We propose a simple solution to use a single Neural Machine Translation ...
11/14/2016 ∙ by Melvin Johnson, et al. ∙
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The Case for Learned Index Structures
Indexes are models: a B-Tree-Index can be seen as a model to map a key t...
12/04/2017 ∙ by Tim Kraska, et al. ∙
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In-Datacenter Performance Analysis of a Tensor Processing Unit
Many architects believe that major improvements in cost-energy-performan...
04/16/2017 ∙ by Norman P. Jouppi, et al. ∙
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Microscope 2.0: An Augmented Reality Microscope with Real-time Artificial Intelligence Integration
The brightfield microscope is instrumental in the visual examination of ...
11/21/2018 ∙ by Po-Hsuan Cameron Chen, et al. ∙
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