Literature on Neural Architecture Search

Maintained by Difan Deng and Marius Lindauer.

The following list considers papers related to neural architecture search. It is by no means complete. If you miss a paper on the list, please let us know.

Please note that although NAS methods steadily improve, the quality of empirical evaluations in this field are still lagging behind compared to other areas in machine learning, AI and optimization. We would therefore like to share some best practices for empirical evaluations of NAS methods, which we believe will facilitate sustained and measurable progress in the field. If you are interested in a teaser, please read our blog post or directly jump to our checklist.


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2018

46.

Gordon, Ariel; Eban, Elad; Nachum, Ofir; Chen, Bo; Wu, Hao; Yang, Tien-Ju; Choi, Edward

MorphNet - Fast & Simple Resource-Constrained Structure Learning of Deep Networks Inproceedings

pp. 1586-1595, 2018.

Links | BibTeX

45.

Ahmed, Karim; Torresani, Lorenzo

MaskConnect - Connectivity Learning by Gradient Descent Inproceedings

pp. 362-378, 2018.

Links | BibTeX

44.

Schrimpf, Martin; Merity, Stephen; Bradbury, James; Socher, Richard

A Flexible Approach to Automated RNN Architecture Generation Inproceedings

2018.

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43.

Suganuma, Masanori; Shirakawa, Shinichi; Nagao, Tomoharu

A Genetic Programming Approach to Designing Convolutional Neural Network Architectures Inproceedings

pp. 5369-5373, 2018.

Links | BibTeX

42.

Zhong, Zhao; Yan, Junjie; Wu, Wei; Shao, Jing; Liu, Cheng-Lin

Practical Block-Wise Neural Network Architecture Generation Inproceedings

pp. 2423-2432, 2018.

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41.

Baker, Bowen; Gupta, Otkrist; Raskar, Ramesh; Naik, Nikhil

Accelerating Neural Architecture Search using Performance Prediction Inproceedings

2018.

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40.

Liu, Hanxiao; Simonyan, Karen; Vinyals, Oriol; Fernando, Chrisantha; Kavukcuoglu, Koray

Hierarchical Representations for Efficient Architecture Search Inproceedings

2018.

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39.

Zoph, Barret; Vasudevan, Vijay; Shlens, Jonathon; Le, Quoc V

Learning Transferable Architectures for Scalable Image Recognition Inproceedings

pp. 8697-8710, 2018.

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38.

Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank

Simple and efficient architecture search for Convolutional Neural Networks Inproceedings

2018.

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37.

Hazan, Elad; Klivans, Adam R; Yuan, Yang

Hyperparameter optimization - a spectral approach Inproceedings

2018.

Links | BibTeX

36.

Brock, Andrew; Lim, Theodore; Ritchie, James M; Weston, Nick

SMASH - One-Shot Model Architecture Search through HyperNetworks Inproceedings

2018.

Links | BibTeX

35.

Cai, Han; Chen, Tianyao; Zhang, Weinan; Yu, Yong; Wang, Jun

Efficient Architecture Search by Network Transformation Inproceedings

pp. 2787-2794, 2018.

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2017

34.

Sun, Yanan; Xue, Bing; Zhang, Mengjie

A Particle Swarm Optimization-based Flexible Convolutional Auto-Encoder for Image Classification Technical Report

, 2017.

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33.

Negrinho, Renato; Gordon, Geoffrey J

DeepArchitect - Automatically Designing and Training Deep Architectures Technical Report

, 2017.

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32.

Real, Esteban; Moore, Sherry; Selle, Andrew; Saxena, Saurabh; Suematsu, Yutaka Leon; Tan, Jie; Le, Quoc V; Kurakin, Alexey

Large-Scale Evolution of Image Classifiers Inproceedings

pp. 2902-2911, 2017.

Links | BibTeX

31.

Bello, Irwan; Zoph, Barret; Vasudevan, Vijay; Le, Quoc V

Neural Optimizer Search with Reinforcement Learning Inproceedings

pp. 459-468, 2017.

Links | BibTeX

30.

Wistuba, Martin

Finding Competitive Network Architectures Within a Day Using UCT Technical Report

, 2017.

Links | BibTeX

29.

Cortes, Corinna; Gonzalvo, Xavier; Kuznetsov, Vitaly; Mohri, Mehryar; Yang, Scott

AdaNet - Adaptive Structural Learning of Artificial Neural Networks Inproceedings

pp. 874-883, 2017.

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28.

Baker, Bowen; Gupta, Otkrist; Naik, Nikhil; Raskar, Ramesh

Designing Neural Network Architectures using Reinforcement Learning Inproceedings

2017.

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27.

Klein, Aaron; Falkner, Stefan; Springenberg, Jost Tobias; Hutter, Frank

Learning Curve Prediction with Bayesian Neural Networks Inproceedings

2017.

Links | BibTeX

26.

Li, Lisha; Jamieson, Kevin G; DeSalvo, Giulia; Rostamizadeh, Afshin; Talwalkar, Ameet

Hyperband - A Novel Bandit-Based Approach to Hyperparameter Optimization Journal Article

18 , pp. 185:1-185:52, 2017.

Links | BibTeX

25.

Chang, Hao

Skin cancer reorganization and classification with deep neural network Technical Report

2017.

Links | BibTeX

24.

Suganuma, Masanori; Shirakawa, Shinichi; Nagao, Tomoharu

A Genetic Programming Approach to Designing Convolutional Neural Network Architectures Technical Report

2017.

Links | BibTeX

23.

Chang, Hao

Skin cancer reorganization and classification with deep neural network Technical Report

2017.

Links | BibTeX

22.

Kani, Nagoor J; Elsheikh, Ahmed H

DR-RNN: A deep residual recurrent neural network for model reduction Technical Report

2017.

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2016

21.

Vu, Ngoc Thang; Adel, Heike; Gupta, Pankaj; Schütze, Hinrich

Combining Recurrent and Convolutional Neural Networks for Relation Classification Technical Report

2016.

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20.

Chen, Long; Zhang, Hanwang; Xiao, Jun; Nie, Liqiang; Shao, Jian; Liu, Wei; Chua, Tat-Seng

SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning Technical Report

2016.

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19.

Smithson, Sean C; Yang, Guang; Gross, Warren J; Meyer, Brett H

Neural networks designing neural networks - multi-objective hyper-parameter optimization Inproceedings

pp. 104, 2016.

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18.

Saxena, Shreyas; Verbeek, Jakob

Convolutional Neural Fabrics Inproceedings

pp. 4053-4061, 2016.

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17.

Loshchilov, Ilya; Hutter, Frank

CMA-ES for Hyperparameter Optimization of Deep Neural Networks Technical Report

, 2016.

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16.

Chen, Tianqi; Goodfellow, Ian J; Shlens, Jonathon

Net2Net - Accelerating Learning via Knowledge Transfer Inproceedings

2016.

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15.

Chen, Justin

Combinatorially Generated Piecewise Activation Functions Technical Report

2016.

Links | BibTeX

2015

14.

Young, Steven R; Rose, Derek C; Karnowski, Thomas P; Lim, Seung-Hwan; Patton, Robert M

Optimizing deep learning hyper-parameters through an evolutionary algorithm Inproceedings

pp. 4:1-4:5, 2015.

Links | BibTeX

13.

Kulish, Vadym V; Malyi, Oleksandr I; Persson, Clas; Wu, Ping

Evaluation of Phosphorene as Anode Material for Na-ion Batteries from First Principles Technical Report

2015.

Links | BibTeX

2013

12.

Lopez, Pablo; Fernandez, David; Marin-Perez, Rafael; Jara, Antonio J; Gomez-Skarmeta, Antonio F

Scalable Oriented-Service Architecture for Heterogeneous and Ubiquitous IoT Domains Technical Report

2013.

Links | BibTeX

11.

Fister, Iztok; Jr., Iztok Fister; Yang, Xin-She; Brest, Janez

A comprehensive review of firefly algorithms Technical Report

2013.

Links | BibTeX

2012

10.

Anas, M; Javaid, N; Mahmood, A; Raza, S M; Qasim, U; Khan, Z A

Minimizing Electricity Theft using Smart Meters in AMI Technical Report

2012.

Links | BibTeX

9.

Snoek, Jasper; Larochelle, Hugo; Adams, Ryan P

Practical Bayesian Optimization of Machine Learning Algorithms Inproceedings

pp. 2960-2968, 2012.

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2009

8.

Stanley, Kenneth O; D'Ambrosio, David B; Gauci, Jason

A Hypercube-Based Encoding for Evolving Large-Scale Neural Networks Journal Article

15 (2), pp. 185-212, 2009.

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7.

Jaffres-Runser, Katia; Gorce, Jean-Marie; Comaniciu, Cristina

A multiobjective Tabu framework for the optimization and evaluation of wireless systems Technical Report

2009.

Links | BibTeX

2008

6.

Floreano, Dario; Dürr, Peter; Mattiussi, Claudio

Neuroevolution - from architectures to learning Journal Article

1 (1), pp. 47-62, 2008.

Links | BibTeX

2005

5.

Czarnowski, Ireneusz; Jedrzejowicz, Piotr

An Agent-Based PLA for the Cascade Correlation Learning Architecture Inproceedings

pp. 197-202, 2005.

Links | BibTeX

2004

4.

Roy, N K; Potter, Walter D; Landau, D P

Designing Polymer Blends Using Neural Networks, Genetic Algorithms, and Markov Chains Journal Article

20 (3), pp. 215-229, 2004.

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1994

3.

Angeline, Peter J; Saunders, Gregory M; Pollack, Jordan B

An evolutionary algorithm that constructs recurrent neural networks Journal Article

5 (1), pp. 54-65, 1994.

Links | BibTeX

1990

2.

Kitano, Hiroaki

Designing Neural Networks Using Genetic Algorithms with Graph Generation System Journal Article

4 (4), 1990.

Links | BibTeX

1988

1.

Tenorio, Manoel Fernando; Lee, Wei-Tsih

Self Organizing Neural Networks for the Identification Problem Inproceedings

pp. 57-64, 1988.

Links | BibTeX

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