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Supervised learning based algorithm selection for deep neural networks
Shaohuai Shi
, Pengfei Xu
, Xiaowen CHU
Department of Computer Science
Research output
:
Chapter in book/report/conference proceeding
›
Conference proceeding
›
peer-review
2
Citations (Scopus)
Overview
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Dive into the research topics of 'Supervised learning based algorithm selection for deep neural networks'. Together they form a unique fingerprint.
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Keyphrases
Learning Algorithm
100%
Supervised Learning
100%
Caffe
100%
Deep Neural Network
100%
Algorithm Selection
100%
Library Function
100%
NVIDIA
66%
Deep Learning System
66%
CuBLAS
66%
Prediction Accuracy
33%
Popular
33%
Selection Strategy
33%
Performance Improvement
33%
Low Computational
33%
Computation Overhead
33%
Computing Power
33%
Training Time
33%
Hereafter
33%
Training Process
33%
Suboptimal Performance
33%
Gradient Boosting Decision Tree
33%
Matrix Transposition
33%
Modern Hardware
33%
Fully Connected Deep Neural Network
33%
Hardware Accelerator
33%
Out-of-position
33%
Computer Science
Supervised Learning
100%
Deep Neural Network
100%
Algorithm Selection
100%
Library Function
100%
Graphics Processing Unit
66%
Deep Learning Method
66%
Learning Platform
66%
Experimental Result
33%
Performance Improvement
33%
Computing Power
33%
Open Source
33%
Decision Tree
33%
Prediction Accuracy
33%
Training Process
33%
Hardware Accelerator
33%