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Learning One-hidden-layer ReLU Networks via Gradient Descent
Xiao Zhang
, Yaodong Yu
,
Lingxiao Wang
, Quanquan Gu
Research output
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Contribution to conference
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Paper
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peer-review
Overview
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Dive into the research topics of 'Learning One-hidden-layer ReLU Networks via Gradient Descent'. Together they form a unique fingerprint.
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Keyphrases
Hidden Layer
100%
Gradient Descent
100%
Rectified Linear Unit (ReLU)
100%
Neural Network
66%
Statistical Errors
33%
Activation Function
33%
Numerical Experiments
33%
Teacher Networks
33%
Gaussian Distribution
33%
Linear Growth Rate
33%
Empirical Risk Minimization
33%
Recovery Guarantee
33%
Practical Learning
33%
Mathematics
Neural Network
100%
Gaussian Distribution
50%
Tensor
50%
Statistical Error
50%
Numerical Experiment
50%
Empirical Risk Minimization
50%
Computer Science
Gradient Descent
100%
ReLU Function
100%
Neural Network
33%
Activation Function
33%
Risk Minimization
33%
Layer Neural Network
33%