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Neural Architecture Search (NAS) has shown great potentials in finding better neural network designs.
A New Method of Locating the Maximum Point of an Arbitrary Multipeak Curve in the Presence of Noise
H. Kushner · 1963
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A Generalised Logit-Normal Distribution
R Mead · 1965
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The application of Bayesian methods for seeking the extremum
J. Mockus, V. Tiesis, and A. Zilinskas · 1978
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Building a Large Annotated Corpus of English: The Penn Treebank
M. Marcus, B. Santorini, and M. Marcinkiewicz · 1993
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Pattern Recognition and Machine Learning
C. Bishop · 2006
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The Graph Neural Network Model
F. Scarselli, M. Gori, A. Tsoi, M. Hagenbuchner, and G. Monfardini · 2008
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L. Li, K. Li, and L. Fei-Fei · 2009
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Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
N. Srinivas, A. Krause, S. Kakade, and M. Seeger · 2009
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Practical Bayesian Optimization of Machine Learning Algorithms
J. Snoek, H. Larochelle, and R. Adams · 2012
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Adam: A Method for Stochastic Optimization
D. Kingma and J. Ba · 2014
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Taking the Human Out of the Loop: A Review of Bayesian Optimization
B. Shahriari, K. Swersky, Z. Wang, R. Adams, and N. De Freitas · 2015
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Scalable Bayesian Optimization Using Deep Neural Networks
J. Snoek, O. Rippel, K. Swersky, R. Kiros, N. Satish, N. Sundaram, M. Patwary, M. Prabhat, and R. Adams · 2015
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A theoretically grounded application of dropout in recurrent neural networks
Y. Gal and Z. Ghahramani · 2016
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Semi-Supervised Classification with Graph Convolutional Networks
T. Kipf and M. Welling · 2016
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Improved Regularization of Convolutional Neural Networks with Cutout
T. DeVries and G. Taylor · 2017
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Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling
H. Inan, K. Khosravi, and R. Socher · 2017
Cited alongside, same era.
Focal Loss for Dense Object Detection
T. Lin, P. Goyal, R. Girshick, K. He, and P. Dollár · 2017
Cited alongside, same era.
Neural Architecture Search with Reinforcement Learning
B. Zoph and Q. Le · 2017
Cited alongside, same era.
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
K. Kandasamy, W. Neiswanger, J. Schneider, B. Poczos, and E. Xing · 2018
Cited alongside, same era.
Progressive Neural Architecture Search
C. Liu, B. Zoph, M. Neumann, J. Shlens, W. Hua, L. Li, L. Fei-Fei, A. Yuille, J. Huang, and K. Murphy · 2018
Cited alongside, same era.
Neural Architecture Optimization
R. Luo, F. Tian, T. Qin, E. Chen, and T. Liu · 2018
Cited alongside, same era.
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
C. Liu, L. Chen, F. Schroff, H. Adam, W. Hua, A. Yuille, and L. Fei-Fei · 2019
Closest in time.
DARTS: Differentiable Architecture Search
H. Liu, K. Simonyan, and Y. Yang · 2019
Closest in time.
Regularized Evolution for Image Classifier Architecture Search
E. Real, A. Aggarwal, Y. Huang, and Q. Le · 2019
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The Evolved Transformer
D. So, Q. Le, and C. Liang · 2019
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Energy and Policy Considerations for Deep Learning in NLP
E. Strubell, A. Ganesh, and A. McCallum · 2019
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Sample-Efficient Neural Architecture Search by Learning Action Space
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Exploring Neural Architecture Search for Language Tasks
M. Luong, D. Dohan, A. Yu, Q. Le, B. Zoph, and V. Vasudevan · 2018
Cited alongside, same era.
Efficient Neural Architecture Search via Parameter Sharing
H. Pham, M. Guan, B. Zoph, Q. Le, and J. Dean · 2018
Cited alongside, same era.
Learning Transferable Architectures for Scalable Image Recognition
B. Zoph, V. Vasudevan, J. Shlens, and Q. Le · 2018
Cited alongside, same era.
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
Y. Akimoto, S. Shirakawa, N. Yoshinari, K. Uchida, S. Saito, and K. Nishida · 2019
Cited alongside, same era.
DetNAS: Neural Architecture Search on Object Detection
Y. Chen, T. Yang, X. Zhang, G. Meng, C. Pan, and J. Sun · 2019
Cited alongside, same era.
Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
X. Chu, B. Zhang, H. Ma, R. Xu, J. Li, and Q. Li · 2019
Cited alongside, same era.
L. Wang, S. Xie, T. Li, R. Fonseca, and Y. Tian · 2019
Closest in time.
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search
L. Wang, Y. Zhao, Y. Jinnai, Y. Tian, and R. Fonseca · 2019
Closest in time.
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
C. White, W. Neiswanger, and Y. Savani · 2019
Closest in time.
SNAS: Stochastic Neural Architecture Search
S. Xie, H. Zheng, C. Liu, and L. Lin · 2019
Closest in time.
NAS-Bench-101: Towards Reproducible Neural Architecture Search
C. Ying, A. Klein, E. Christiansen, E. Real, K. Murphy, and F. Hutter · 2019
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Graph HyperNetworks for Neural Architecture Search
C. Zhang, M. Ren, and R. Urtasun · 2019
Closest in time.
BayesNAS: A Bayesian Approach for Neural Architecture Search
H. Zhou, M. Yang, J. Wang, and W. Pan · 2019
Closest in time.
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search
X. Dong and Y. Yang · 2020
Closest in time.
NAS evaluation is frustratingly hard
A. Yang, P. Esperança, and F. Carlucci · 2020
Closest in time.