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.


1147 entries « 22 of 23 »

2018

97.

Lindqvist, Blerta; Sugrim, Shridatt; Izmailov, Rauf

AutoGAN: Robust Classifier Against Adversarial Attacks Technical Report

2018.

Links | BibTeX

96.

Sun, Man-Chin; Hsu, Shih-Huan; Yang, Min-Chun; Chien, Jen-Hsien

Context-aware Cascade Attention-based RNN for Video Emotion Recognition Technical Report

2018.

Links | BibTeX

95.

Ritter, Hippolyt; Botev, Aleksandar; Barber, David

Online Structured Laplace Approximations For Overcoming Catastrophic Forgetting Technical Report

2018.

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94.

Zhang, Honglei; Kiranyaz, Serkan; Gabbouj, Moncef

Finding Better Topologies for Deep Convolutional Neural Networks by Evolution Technical Report

2018.

Links | BibTeX

93.

Kandasamy, Kirthevasan; Neiswanger, Willie; Schneider, Jeff; Poczos, Barnabas; Xing, Eric

Neural Architecture Search with Bayesian Optimisation and Optimal Transport Technical Report

2018.

Links | BibTeX

92.

Hamraz, Hamid; Jacobs, Nathan B; Contreras, Marco A; Clark, Chase H

Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees Technical Report

2018.

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91.

Perez-Rua, Juan-Manuel; Baccouche, Moez; Pateux, Stephane

Efficient Progressive Neural Architecture Search Technical Report

2018.

Links | BibTeX

90.

Deglint, Jason L; Jin, Chao; Chao, Angela; Wong, Alexander

The feasibility of automated identification of six algae types using neural networks and fluorescence-based spectral-morphological features Technical Report

2018.

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89.

Kamath, Purushotham; Singh, Abhishek; Dutta, Debo

AMLA: an AutoML frAmework for Neural Network Design Technical Report

2018.

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88.

de Laroussilhe, Quentin; Jastrzebski, Stanislaw; Houlsby, Neil; Gesmundo, Andrea

Neural Architecture Search Over a Graph Search Space Technical Report

, 2018.

Links | BibTeX

87.

Jaâfra, Yesmina; Laurent, Jean Luc; Deruyver, Aline; Naceur, Mohamed Saber

A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search Technical Report

, 2018.

Links | BibTeX

86.

Wu, Bichen; Wang, Yanghan; Zhang, Peizhao; Tian, Yuandong; Vajda, Peter; Keutzer, Kurt

Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search Technical Report

, 2018.

Links | BibTeX

85.

Wang, Bin; Sun, Yanan; Xue, Bing; Zhang, Mengjie

Evolving Deep Convolutional Neural Networks by Variable-Length Particle Swarm Optimization for Image Classification Inproceedings

pp. 1-8, 2018.

Links | BibTeX

84.

Wang, Bin; Sun, Yanan; Xue, Bing; Zhang, Mengjie

A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification Inproceedings

pp. 237-250, 2018.

Links | BibTeX

83.

Maziarz, Krzysztof; Khorlin, Andrey; de Laroussilhe, Quentin; Gesmundo, Andrea

Evolutionary-Neural Hybrid Agents for Architecture Search Technical Report

, 2018.

Links | BibTeX

82.

Chen, Yukang; Meng, Gaofeng; Zhang, Qian; Zhang, Xinbang; Song, Liangchen; Xiang, Shiming; Pan, Chunhong

Joint Neural Architecture Search and Quantization Technical Report

, 2018.

Links | BibTeX

81.

Wong, Catherine; Houlsby, Neil; Lu, Yifeng; Gesmundo, Andrea

Transfer Learning with Neural AutoML Inproceedings

pp. 8366-8375, 2018.

Links | BibTeX

80.

Fielding, Ben; Zhang, Li

Evolving Image Classification Architectures With Enhanced Particle Swarm Optimisation Journal Article

6 , pp. 68560-68575, 2018.

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79.

Lu, Zhichao; Whalen, Ian; Boddeti, Vishnu; Dhebar, Yashesh D; Deb, Kalyanmoy; Goodman, Erik D; Banzhaf, Wolfgang

NSGA-NET - A Multi-Objective Genetic Algorithm for Neural Architecture Search Technical Report

, 2018.

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78.

Zhang, Xinbang; Huang, Zehao; Wang, Naiyan

You Only Search Once - Single Shot Neural Architecture Search via Direct Sparse Optimization Technical Report

, 2018.

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77.

Sun, Yanan; Xue, Bing; Zhang, Mengjie

Automatically Evolving CNN Architectures Based on Blocks Technical Report

, 2018.

Links | BibTeX

76.

Mitschke, Norbert; Heizmann, Michael; Noffz, Klaus-Henning; Wittmann, Ralf

Gradient Based Evolution to Optimize the Structure of Convolutional Neural Networks Inproceedings

pp. 3438-3442, 2018.

Links | BibTeX

75.

Cheng, An-Chieh; Dong, Jin-Dong; Hsu, Chi-Hung; Chang, Shu-Huan; Sun, Min; Chang, Shih-Chieh; Pan, Jia-Yu; Chen, Yu-Ting; Wei, Wei; Juan, Da-Cheng

Searching toward pareto-optimal device-aware neural architectures Inproceedings

pp. 136, 2018.

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74.

Chen, Junkun; Chen, Kaiyu; Chen, Xinchi; Qiu, Xipeng; Huang, Xuanjing

Exploring Shared Structures and Hierarchies for Multiple NLP Tasks Technical Report

, 2018.

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73.

Zhong, Zhao; Yang, Zichen; Deng, Boyang; Yan, Junjie; Wu, Wei; Shao, Jing; Liu, Cheng-Lin

BlockQNN - Efficient Block-wise Neural Network Architecture Generation Technical Report

, 2018.

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72.

Zela, Arber; Klein, Aaron; Falkner, Stefan; Hutter, Frank

Towards Automated Deep Learning - Efficient Joint Neural Architecture and Hyperparameter Search Technical Report

, 2018.

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71.

Mortazi, Aliasghar; Bagci, Ulas

Automatically Designing CNN Architectures for Medical Image Segmentation Inproceedings

pp. 98-106, 2018.

Links | BibTeX

70.

Hsu, Chi-Hung; Chang, Shu-Huan; Juan, Da-Cheng; Pan, Jia-Yu; Chen, Yu-Ting; Wei, Wei; Chang, Shih-Chieh

MONAS - Multi-Objective Neural Architecture Search using Reinforcement Learning Technical Report

, 2018.

Links | BibTeX

69.

Cai, Han; Yang, Jiacheng; Zhang, Weinan; Han, Song; Yu, Yong

Path-Level Network Transformation for Efficient Architecture Search Inproceedings

pp. 677-686, 2018.

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68.

Prellberg, Jonas; Kramer, Oliver

Lamarckian Evolution of Convolutional Neural Networks Inproceedings

pp. 424-435, 2018.

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67.

Wistuba, Martin

Deep Learning Architecture Search by Neuro-Cell-Based Evolution with Function-Preserving Mutations Inproceedings

pp. 243-258, 2018.

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66.

Rohekar, Raanan Yehezkel Y; Nisimov, Shami; Gurwicz, Yaniv; Koren, Guy; Novik, Gal

Constructing Deep Neural Networks by Bayesian Network Structure Learning Inproceedings

pp. 3051-3062, 2018.

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65.

Jin, Haifeng; Song, Qingquan; Hu, Xia

Efficient Neural Architecture Search with Network Morphism Technical Report

, 2018.

Links | BibTeX

64.

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

Multi-objective Architecture Search for CNNs Technical Report

, 2018.

Links | BibTeX

63.

Huang, Siyu; Li, Xi; Cheng, Zhiqi; Zhang, Zhongfei; Hauptmann, Alexander G

GNAS - A Greedy Neural Architecture Search Method for Multi-Attribute Learning Inproceedings

pp. 2049-2057, 2018.

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62.

Liang, Jason Zhi; Meyerson, Elliot; Miikkulainen, Risto

Evolutionary architecture search for deep multitask networks Inproceedings

pp. 466-473, 2018.

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61.

Rawal, Aditya; Miikkulainen, Risto

From Nodes to Networks - Evolving Recurrent Neural Networks Technical Report

, 2018.

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60.

Kamath, Purushotham; Singh, Abhishek; Dutta, Debo

Neural Architecture Construction using EnvelopeNets Technical Report

, 2018.

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59.

Wong, Catherine; Houlsby, Neil; Lu, Yifeng; Gesmundo, Andrea

Transfer Automatic Machine Learning Technical Report

, 2018.

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58.

Kandasamy, Kirthevasan; Neiswanger, Willie; Schneider, Jeff; Póczos, Barnabás; Xing, Eric P

Neural Architecture Search with Bayesian Optimisation and Optimal Transport Inproceedings

pp. 2020-2029, 2018.

Links | BibTeX

57.

Pham, Hieu; Guan, Melody Y; Zoph, Barret; Le, Quoc V; Dean, Jeff

Efficient Neural Architecture Search via Parameter Sharing Inproceedings

pp. 4092-4101, 2018.

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56.

Dutta, Jayanta K; Liu, Jiayi; Kurup, Unmesh; Shah, Mohak

Effective Building Block Design for Deep Convolutional Neural Networks using Search Technical Report

, 2018.

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55.

Wang, Jiazhuo; Xu, Jason; Wang, Xuejun

Combination of Hyperband and Bayesian Optimization for Hyperparameter Optimization in Deep Learning Technical Report

, 2018.

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54.

Lorenzo, Pablo Ribalta; Nalepa, Jakub

Memetic evolution of deep neural networks Inproceedings

pp. 505-512, 2018.

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53.

Bender, Gabriel; Kindermans, Pieter-Jan; Zoph, Barret; Vasudevan, Vijay; Le, Quoc V

Understanding and Simplifying One-Shot Architecture Search Inproceedings

pp. 549-558, 2018.

Links | BibTeX

52.

Dong, Jin-Dong; Cheng, An-Chieh; Juan, Da-Cheng; Wei, Wei; Sun, Min

PPP-Net - Platform-aware Progressive Search for Pareto-optimal Neural Architectures Inproceedings

2018.

Links | BibTeX

51.

Hinz, Tobias; Navarro-Guerrero, Nicolás; Magg, Sven; Wermter, Stefan

Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks Journal Article

17 (2), pp. 1850008:1-1850008:15, 2018.

Links | BibTeX

50.

Bennani-Smires, Kamil; Musat, Claudiu; Hossmann, Andreea; Baeriswyl, Michael

GitGraph - from Computational Subgraphs to Smaller Architecture Search Spaces Inproceedings

2018.

Links | BibTeX

49.

Ashok, Anubhav; Rhinehart, Nicholas; Beainy, Fares; Kitani, Kris M

N2N learning - Network to Network Compression via Policy Gradient Reinforcement Learning Inproceedings

2018.

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48.

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

1147 entries « 22 of 23 »