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Efficient hyperparameter or architecture search methods have shown remarkable results, but each of them is only applicable to searching for either hyperparameters (HPs) or architectures.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Automatic parameter selection by minimizing estimated error
Ron Kohavi and George H John · 1995
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Efficient global optimization of expensive black-box functions
Donald R Jones, Matthias Schonlau, and William J Welch · 1998
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ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Automated configuration of algorithms for solving hard computational problems
Frank Hutter · 2009
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Sequential model-based optimization for general algorithm configuration
Frank Hutter, Holger H Hoos, and Kevin Leyton-Brown · 2011
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Random search for hyper-parameter optimization
James Bergstra and Yoshua Bengio · 2012
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Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves
Tobias Domhan, Jost Tobias Springenberg, and Frank Hutter · 2015
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Gradient-based hyperparameter optimization through reversible learning
Dougal Maclaurin, David Duvenaud, and Ryan Adams · 2015
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Taking the human out of the loop: A review of bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando De Freitas · 2015
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Scalable bayesian optimization using deep neural networks
Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Mostofa Patwary, Mr Prabhat, and Ryan Adams · 2015
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Hyperparameter optimization with approximate gradient
Fabian Pedregosa · 2016
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Designing neural network architectures using reinforcement learning
Bowen Baker, Otkrist Gupta, Nikhil Naik, and Ramesh Raskar · 2017
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Google vizier: A service for black-box optimization
Daniel Golovin, Benjamin Solnik, Subhodeep Moitra, Greg Kochanski, John Karro, and D Sculley · 2017
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Population based training of neural networks
Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, et al · 2017
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Hyperband: A novel bandit-based approach to hyperparameter optimization
Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, and Ameet Talwalkar · 2017
Cited alongside, same era.
Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
Cited alongside, same era.
Neural architecture search with reinforcement learning
Barret Zoph and Quoc V Le · 2017
Cited alongside, same era.
Online learning rate adaptation with hypergradient descent
Atılım Güneş Baydin, Robert Cornish, David Martínez Rubio, Mark Schmidt, and Frank Wood · 2018
Cited alongside, same era.
Efficient neural architecture search via parameter sharing
Hieu Pham, Melody Y Guan, Barret Zoph, Quoc V Le, and Jeff Dean · 2018
Cited alongside, same era.
MobileNetV2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V Le · 2019
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Truncated back-propagation for bilevel optimization
Amirreza Shaban, Ching-An Cheng, Nathan Hatch, and Byron Boots · 2019
Later among the works it cites.
EfficientNet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc Le · 2019
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MNasNet: Platform-aware neural architecture search for mobile
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, and Quoc V Le · 2019
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FBNet: Hardware-aware efficient convnet design via differentiable neural architecture search
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, and Kurt Keutzer · 2019
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SNAS: stochastic neural architecture search
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Cited alongside, same era.
Towards automated deep learning: Efficient joint neural architecture and hyperparameter search
Arber Zela, Aaron Klein, Stefan Falkner, and Frank Hutter · 2018
Cited alongside, same era.
mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2018
Cited alongside, same era.
Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le · 2018
Cited alongside, same era.
ProxylessNAS: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2019
Cited alongside, same era.
Searching for a robust neural architecture in four gpu hours
Xuanyi Dong and Yi Yang · 2019
Cited alongside, same era.
Automated Machine Learning
Frank Hutter, Lars Kotthoff, and Joaquin Vanschoren · 2019
Cited alongside, same era.
Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin · 2019
Later among the works it cites.
Can weight sharing outperform random architecture search? an investigation with tunas
Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, and Quoc V Le · 2020
Closest in time.
Once for all: Train one network and specialize it for efficient deployment
Han Cai, Chuang Gan, and Song Han · 2020
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FBNetV3: Joint architecture-recipe search using neural acquisition function
Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, et al · 2020
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Mixed-variable bayesian optimization
Erik A Daxberger, Anastasia Makarova, Matteo Turchetta, and Andreas Krause · 2020
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Random search and reproducibility for neural architecture search
Liam Li and Ameet Talwalkar · 2020
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Optimizing millions of hyperparameters by implicit differentiation
Jonathan Lorraine, Paul Vicol, and David Duvenaud · 2020
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Bayesian optimisation over multiple continuous and categorical inputs
Binxin Ru, Ahsan Alvi, Vu Nguyen, Michael A Osborne, and Stephen Roberts · 2020
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FBNetV2: Differentiable neural architecture search for spatial and channel dimensions
Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, et al · 2020
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Understanding and robustifying differentiable architecture search
Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, and Frank Hutter · 2020
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