Literature on Neural Architecture Search

@techreport{White2019_fwp,

title = {BANANAS - Bayesian Optimization with Neural Architectures for Neural Architecture Search},

author = {Colin White and Willie Neiswanger and Yash Savani},

url = {https://arxiv.org/abs/1808.07233},

year  = {2019},

date = {2019-01-01},

volume = {abs/1910.11858},

key = {journals/corr/abs-1910-11858},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Wistuba2019_ksp,

title = {A Survey on Neural Architecture Search},

author = {Martin Wistuba and Ambrish Rawat and Tejaswini Pedapati},

url = {https://arxiv.org/abs/1808.05377},

year  = {2019},

date = {2019-01-01},

volume = {abs/1905.01392},

key = {journals/corr/abs-1905-01392},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Cao2019_skt,

title = {Learnable Embedding Space for Efficient Neural Architecture Compression},

author = {Shengcao Cao and Xiaofang Wang and Kris M Kitani},

url = {https://www.semanticscholar.org/paper/Bayesian-Optimization-Combined-with-Successive-for-Wistuba/ddb182533c91f0941f088e1e298c52a111253554},

year  = {2019},

date = {2019-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Mendoza2019_hql,

title = {Towards Automatically-Tuned Deep Neural Networks},

author = {Hector Mendoza and Aaron Klein and Matthias Feurer and Jost Tobias Springenberg and Matthias Urban and Michael Burkart and Maximilian Dippel and Marius Lindauer and Frank Hutter},

url = {http://proceedings.mlr.press/v64/mendoza_towards_2016.html},

doi = {10.1007/978-3-030-05318-5_7},

year  = {2019},

date = {2019-01-01},

pages = {135-149},

key = {books/sp/19/MendozaKFSUBDLH19},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Lindqvist2018_sqh,

title = {AutoGAN: Robust Classifier Against Adversarial Attacks},

author = {Blerta Lindqvist and Shridatt Sugrim and Rauf Izmailov},

url = {https://link.springer.com/article/10.1007/s00500-020-05446-x},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Sun2018_gep,

title = {Context-aware Cascade Attention-based RNN for Video Emotion Recognition},

author = {Man-Chin Sun and Shih-Huan Hsu and Min-Chun Yang and Jen-Hsien Chien},

url = {http://users.cecs.anu.edu.au/~Tom.Gedeon/conf/ABCs2020/paper/ABCs2020_paper_v2_123.pdf},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Ritter2018_nko,

title = {Online Structured Laplace Approximations For Overcoming Catastrophic 

Forgetting},

author = {Hippolyt Ritter and Aleksandar Botev and David Barber},

url = {https://www.computer.org/csdl/journal/tp/5555/01/09247292/1oslcjvUdHi},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Zhang2018_nhq,

title = {Finding Better Topologies for Deep Convolutional Neural Networks by 

Evolution},

author = {Honglei Zhang and Serkan Kiranyaz and Moncef Gabbouj},

url = {https://ieeexplore.ieee.org/abstract/document/9201169},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Kandasamy2018_skp,

title = {Neural Architecture Search with Bayesian Optimisation and Optimal 

Transport},

author = {Kirthevasan Kandasamy and Willie Neiswanger and Jeff Schneider and Barnabas Poczos and Eric Xing},

url = {http://metalearning.ml/2019/papers/metalearn2019-white.pdf},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Hamraz2018_acx,

title = {Deep learning for conifer/deciduous classification of airborne LiDAR 3D 

point clouds representing individual trees},

author = {Hamid Hamraz and Nathan B Jacobs and Marco A Contreras and Chase H Clark},

url = {https://ieeexplore.ieee.org/abstract/document/9139215},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Perez-Rua2018_hpl,

title = {Efficient Progressive Neural Architecture Search},

author = {Juan-Manuel Perez-Rua and Moez Baccouche and Stephane Pateux},

url = {https://scholarsmine.mst.edu/cgi/viewcontent.cgi?article=3871&context=doctoral_dissertations},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Deglint2018_qrq,

title = {The feasibility of automated identification of six algae types using 

neural networks and fluorescence-based spectral-morphological features},

author = {Jason L Deglint and Chao Jin and Angela Chao and Alexander Wong},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0016003220302076},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Kamath2018_emu,

title = {AMLA: an AutoML frAmework for Neural Network Design},

author = {Purushotham Kamath and Abhishek Singh and Debo Dutta},

url = {http://pkamath.com/publications/papers/amla_automl18.pdf},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Laroussilhe2018_oaa,

title = {Neural Architecture Search Over a Graph Search Space},

author = {Quentin de Laroussilhe and Stanislaw Jastrzebski and Neil Houlsby and Andrea Gesmundo},

url = {https://arxiv.org/abs/1812.10666},

year  = {2018},

date = {2018-01-01},

volume = {abs/1812.10666},

key = {journals/corr/abs-1812-10666},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Jaâfra2018_pka,

title = {A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search},

author = {Yesmina Jaâfra and Jean Luc Laurent and Aline Deruyver and Mohamed Saber Naceur},

url = {https://arxiv.org/abs/1812.07995},

year  = {2018},

date = {2018-01-01},

volume = {abs/1812.07995},

key = {journals/corr/abs-1812-07995},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Wu2018_fph,

title = {Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search},

author = {Bichen Wu and Yanghan Wang and Peizhao Zhang and Yuandong Tian and Peter Vajda and Kurt Keutzer},

url = {https://arxiv.org/abs/1812.00090},

year  = {2018},

date = {2018-01-01},

volume = {abs/1812.00090},

key = {journals/corr/abs-1812-00090},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Maziarz2018_rch,

title = {Evolutionary-Neural Hybrid Agents for Architecture Search},

author = {Krzysztof Maziarz and Andrey Khorlin and Quentin de Laroussilhe and Andrea Gesmundo},

url = {https://arxiv.org/abs/1811.09828},

year  = {2018},

date = {2018-01-01},

volume = {abs/1811.09828},

key = {journals/corr/abs-1811-09828},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Chen2018_naj,

title = {Joint Neural Architecture Search and Quantization},

author = {Yukang Chen and Gaofeng Meng and Qian Zhang and Xinbang Zhang and Liangchen Song and Shiming Xiang and Chunhong Pan},

url = {https://arxiv.org/abs/1811.09426},

year  = {2018},

date = {2018-01-01},

volume = {abs/1811.09426},

key = {journals/corr/abs-1811-09426},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Lu2018_izw,

title = {NSGA-NET - A Multi-Objective Genetic Algorithm for Neural Architecture Search},

author = {Zhichao Lu and Ian Whalen and Vishnu Boddeti and Yashesh D Dhebar and Kalyanmoy Deb and Erik D Goodman and Wolfgang Banzhaf},

url = {https://arxiv.org/abs/1810.03522},

year  = {2018},

date = {2018-01-01},

volume = {abs/1810.03522},

key = {journals/corr/abs-1810-03522},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Zhang2018_xmy,

title = {You Only Search Once - Single Shot Neural Architecture Search via Direct Sparse Optimization},

author = {Xinbang Zhang and Zehao Huang and Naiyan Wang},

url = {https://arxiv.org/abs/1811.01567},

year  = {2018},

date = {2018-01-01},

volume = {abs/1811.01567},

key = {journals/corr/abs-1811-01567},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Sun2018_vwi,

title = {Automatically Evolving CNN Architectures Based on Blocks},

author = {Yanan Sun and Bing Xue and Mengjie Zhang},

url = {https://arxiv.org/abs/1810.11875},

year  = {2018},

date = {2018-01-01},

volume = {abs/1810.11875},

key = {journals/corr/abs-1810-11875},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Chen2018_nlw,

title = {Exploring Shared Structures and Hierarchies for Multiple NLP Tasks},

author = {Junkun Chen and Kaiyu Chen and Xinchi Chen and Xipeng Qiu and Xuanjing Huang},

url = {https://arxiv.org/abs/1808.07658},

year  = {2018},

date = {2018-01-01},

volume = {abs/1808.07658},

key = {journals/corr/abs-1808-07658},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Zhong2018_mlu,

title = {BlockQNN - Efficient Block-wise Neural Network Architecture Generation},

author = {Zhao Zhong and Zichen Yang and Boyang Deng and Junjie Yan and Wei Wu and Jing Shao and Cheng-Lin Liu},

url = {https://arxiv.org/abs/1808.05584},

year  = {2018},

date = {2018-01-01},

volume = {abs/1808.05584},

key = {journals/corr/abs-1808-05584},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Zela2018_ipg,

title = {Towards Automated Deep Learning - Efficient Joint Neural Architecture and Hyperparameter Search},

author = {Arber Zela and Aaron Klein and Stefan Falkner and Frank Hutter},

url = {https://arxiv.org/abs/1807.06906},

year  = {2018},

date = {2018-01-01},

volume = {abs/1807.06906},

key = {journals/corr/abs-1807-06906},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Hsu2018_frh,

title = {MONAS - Multi-Objective Neural Architecture Search using Reinforcement Learning},

author = {Chi-Hung Hsu and Shu-Huan Chang and Da-Cheng Juan and Jia-Yu Pan and Yu-Ting Chen and Wei Wei and Shih-Chieh Chang},

url = {https://arxiv.org/abs/1806.10332},

year  = {2018},

date = {2018-01-01},

volume = {abs/1806.10332},

key = {journals/corr/abs-1806-10332},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Jin2018_qdx,

title = {Efficient Neural Architecture Search with Network Morphism},

author = {Haifeng Jin and Qingquan Song and Xia Hu},

url = {https://arxiv.org/abs/1806.10282},

year  = {2018},

date = {2018-01-01},

volume = {abs/1806.10282},

key = {journals/corr/abs-1806-10282},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Elsken2018_fop,

title = {Multi-objective Architecture Search for CNNs},

author = {Thomas Elsken and Jan Hendrik Metzen and Frank Hutter},

url = {https://arxiv.org/abs/1804.09081},

year  = {2018},

date = {2018-01-01},

volume = {abs/1804.09081},

key = {journals/corr/abs-1804-09081},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Rawal2018_mgh,

title = {From Nodes to Networks - Evolving Recurrent Neural Networks},

author = {Aditya Rawal and Risto Miikkulainen},

url = {https://arxiv.org/abs/1803.04439},

year  = {2018},

date = {2018-01-01},

volume = {abs/1803.04439},

key = {journals/corr/abs-1803-04439},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Kamath2018_eml,

title = {Neural Architecture Construction using EnvelopeNets},

author = {Purushotham Kamath and Abhishek Singh and Debo Dutta},

url = {https://arxiv.org/abs/1803.06744},

year  = {2018},

date = {2018-01-01},

volume = {abs/1803.06744},

key = {journals/corr/abs-1803-06744},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Wong2018_uaa,

title = {Transfer Automatic Machine Learning},

author = {Catherine Wong and Neil Houlsby and Yifeng Lu and Andrea Gesmundo},

url = {https://arxiv.org/abs/1803.02780},

year  = {2018},

date = {2018-01-01},

volume = {abs/1803.02780},

key = {journals/corr/abs-1803-02780},

keywords = {},

pubstate = {published},

tppubtype = {techreport}

}