Bayesian optimization for the design of deep neural networks

2021 ◽  
Author(s):  
Nikolas Giannakis ◽  
Nikolaos Gorgolis ◽  
Ioannis Hatzilygeroudis
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Bayesian Optimization

scholarly journals Basic Enhancement Strategies When Using Bayesian Optimization for Hyperparameter Tuning of Deep Neural Networks

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 52588-52608 ◽  
Author(s):  
Hyunghun Cho ◽  
Yongjin Kim ◽  
Eunjung Lee ◽  
Daeyoung Choi ◽  
Yongjae Lee ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Bayesian Optimization

Deep neural networks trained with heavier data augmentation learn features closer to representations in hIT

2018 ◽  
Author(s):  
Alex Hernández-García ◽  
Johannes Mehrer ◽  
Nikolaus Kriegeskorte ◽  
Peter König ◽  
Tim C. Kietzmann
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Data Augmentation

Representation of adversarial images in deep neural networks and the human brain

2018 ◽  
Author(s):  
Chi Zhang ◽  
Xiaohan Duan ◽  
Ruyuan Zhang ◽  
Li Tong
Keyword(s):  
Neural Networks ◽  
Human Brain ◽  
Deep Neural Networks

Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks

2018 ◽  
Author(s):  
Daniel Povey ◽  
Gaofeng Cheng ◽  
Yiming Wang ◽  
Ke Li ◽  
Hainan Xu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Matrix Factorization ◽  
Deep Neural Networks ◽  
Low Rank ◽  
Rank Matrix ◽  
Low Rank Matrix
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