NAS.bib

% == this file is about neural architecture search (NAS)

@article{NAS-arXiv2018-Elsken,
    title   = {Neural architecture search: A survey},
    author  = {Elsken, Thomas and Metzen, Jan Hendrik and Hutter, Frank},
    journal = {arXiv preprint arXiv:1808.05377},
    year    = {2018},
}

% === reinforcement learning (RL)
%{{{
@inproceedings{NAS-ICML2017-Bello,
    title     = {Neural Optimizer Search with Reinforcement Learning},
    author    = {Bello, Irwan and Zoph, Barret and Vasudevan, Vijay and Le, Quoc V.},
    booktitle = icml,
    pages     = {459--468},
    year      = {2017},
}
@inproceedings{NAS-ICLR2017-Baker,
    title     = {Designing Neural Network Architectures using Reinforcement Learning},
    author    = {Baker, Bowen and Gupta, Otkrist and Naik, Nikhil and Raskar, Ramesh},
    booktitle = iclr,
    year      = {2017},
}
@inproceedings{NAS-ICLR2017-Zoph,
    title     = {Neural Architecture Search with Reinforcement Learning},
    author    = {Zoph, Barret and Le, Quoc},
    booktitle = iclr,
    year      = {2017},
}
@inproceedings{NAS-AAAI2018-Cai,
    title     = {Efficient architecture search by network transformation},
    author    = {Cai, Han and Chen, Tianyao and Zhang, Weinan and Yu, Yong and Wang, Jun},
    booktitle = aaai,
    year      = {2018},
}
@inproceedings{NAS-ICML2018-Pham,
    title     = {Efficient Neural Architecture Search via Parameter Sharing},
    author    = {Pham, Hieu and Guan, Melody Y and Zoph, Barret and Le, Quoc V and Dean, Jeff},
    booktitle = icml,
    year      = {2018},
}
@inproceedings{NAS-ICML2018-Cai,
    title     = {Path-Level Network Transformation for Efficient Architecture Search},
    author    = {Cai, Han and Yang, Jiacheng and Zhang, Weinan and Han, Song and Yu, Yong},
    booktitle = icml,
    year      = {2018},
}
@inproceedings{NAS-CVPR2018-Zoph,
    title     = {Learning Transferable Architectures for Scalable Image Recognition},
    author    = {Zoph, Barret and Vasudevan, Vijay and Shlens, Jonathon and Le, Quoc V},
    booktitle = cvpr,
    year      = {2018},
}
@inproceedings{NAS-CVPR2018-Zhong,
    title     = {Practical Block-wise Neural Network Architecture Generation},
    author    = {Zhong, Zhao and Yan, Junjie and Wu, Wei and Shao, Jing and Liu, Cheng-Lin},
    booktitle = cvpr,
    pages     = {2423--2432},
    year      = {2018},
}
%}}}
% === evolutionary based
@inproceedings{NAS-ICLR2016-Loshchilov,
    title     = {{CMA-ES} for Hyperparameter Optimization of Deep Neural Networks},
    author    = {Loshchilov, Ilya and Hutter, Frank},
    booktitle = iclr,
    year      = {2016},
}
@inproceedings{NAS-ICCV2017-Xie,
    title={Genetic {CNN}},
    author={Xie, Lingxi and Yuille, Alan L},
    booktitle=iccv,
    pages={1388--1397},
    year={2017},
}
@inproceedings{NAS-ICML2017-Real,
    title={Large-Scale Evolution of Image Classifiers},
    author={Real, Esteban and Moore, Sherry and Selle, Andrew and Saxena, Saurabh and Suematsu, Yutaka Leon and Tan, Jie and Le, Quoc V and Kurakin, Alexey},
    booktitle=icml,
    pages={2902--2911},
    year={2017},
}
@inproceedings{NAS-ICLR2018-Liu,
    title={Hierarchical Representations for Efficient Architecture Search},
    author={Liu, Hanxiao and Simonyan, Karen and Vinyals, Oriol and Fernando, Chrisantha and Kavukcuoglu, Koray},
    booktitle=iclr,
    year={2018},
}
% === GP based
@inproceedings{NAS-IJCAI2015-Domhan,
    title={Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves.},
    author={Domhan, Tobias and Springenberg, Jost Tobias and Hutter, Frank},
    booktitle=ijcai,
    pages={3460--8},
    year={2015},
}
@inproceedings{NAS-ISLPED2017-Reagen,
    title={A case for efficient accelerator design space exploration via Bayesian optimization},
    author={Reagen, Brandon and Hern{\'a}ndez-Lobato, Jos{\'e} Miguel and Adolf, Robert and Gelbart, Michael and Whatmough, Paul and Wei, Gu-Yeon and Brooks, David},
    booktitle=islped,
    pages={1--6},
    year={2017},
}
@inproceedings{NAS-arXiv2018-Kandasamy,
    title={Neural architecture search with bayesian optimisation and optimal transport},
    author={Kandasamy, Kirthevasan and Neiswanger, Willie and Schneider, Jeff and Poczos, Barnabas and Xing, Eric},
    booktitle=arxiv,
    year={2018},
}
@inproceedings{NAS-arXiv2018-Jin,
    title={Efficient neural architecture search with network morphism},
    author={Jin, Haifeng and Song, Qingquan and Hu, Xia},
    booktitle=arxiv,
    year={2018},
}
% === bandit based
@inproceedings{NAS-ICLR2017-Li,
    title={Hyperband: Bandit-based configuration evaluation for hyperparameter optimization},
    author={Li, Lisha and Jamieson, Kevin and DeSalvo, Giulia and Rostamizadeh, Afshin and Talwalkar, Ameet},
    booktitle=iclr,
    year={2017},
}
@article{NAS-JMLR2018-Li,
    title={Hyperband: A novel bandit-based approach to hyperparameter optimization},
    author={Li, Lisha and Jamieson, Kevin and DeSalvo, Giulia and Rostamizadeh, Afshin and Talwalkar, Ameet},
    journal=jmlr,
    volume={18},
    pages={1--52},
    year={2018},
}
% === heuristic search
@inproceedings{NAS-ECCV2018-Liu,
    title={Progressive Neural Architecture Search},
    author={Liu, Chenxi and Zoph, Barret and Shlens, Jonathon and Hua, Wei and Li, Li-Jia and Fei-Fei, Li and Yuille, Alan and Huang, Jonathan and Murphy, Kevin},
    booktitle=eccv,
    year={2018},
}
@inproceedings{NAS-ECCV2018-Dong,
    title={{DPP-Net}: Device-aware Progressive Search for Pareto-optimal Neural Architectures},
    author={Dong, Jin-Dong and Cheng, An-Chieh and Juan, Da-Cheng and Wei, Wei and Sun, Min},
    booktitle=eccv,
    year={2018},
}
% TO CLASSIFY
@inproceedings{NAS-ICLR2017-Klein,
    title={Learning curve prediction with Bayesian neural networks},
    author={Klein, Aaron and Falkner, Stefan and Springenberg, Jost Tobias and Hutter, Frank},
    booktitle=iclr,
    year={2017},
}
@inproceedings{NAS-ICML2017-Cortes,
    title={{AdaNet}: Adaptive Structural Learning of Artificial Neural Networks},
    author={Cortes, Corinna and Gonzalvo, Xavier and Kuznetsov, Vitaly and Mohri, Mehryar and Yang, Scott},
    booktitle=icml,
    pages={874--883},
    year={2017},
}