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Neural Architecture Search (NAS) is an emerging topic in machine learning and computer vision.
Single Path One-Shot Neural Architecture Search with Uniform Sampling
Guo, Z.; Zhang, X.; Mu, H.; Heng, W.; Liu, Z.; Wei, Y.; and Sun, J. 2019 · 1904
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Survey on Automated Machine Learning
Zöller, M.; and Huber, M. F. 2019 · 1904
Earlier work this paper cites.
Searching for MobileNetV3
Howard, A.; Sandler, M.; Chu, G.; Chen, L.; Chen, B.; Tan, M.; Wang, W.; Zhu, Y.; Pang, R.; Vasudevan, V.; Le, Q. V.; and Adam, H. 2019 · 1905
Earlier work this paper cites.
Pc-darts: Partial channel connections for memory-efficient differentiable architecture search
Xu, Y.; Xie, L.; Zhang, X.; Chen, X.; Qi, G.-J.; Tian, Q.; and Xiong, H. 2019 · 1907
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SqueezeNAS: Fast neural architecture search for faster semantic segmentation
Shaw, A.; Hunter, D.; Iandola, F. N.; and Sidhu, S. 2019 · 1908
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Understanding and Robustifying Differentiable Architecture Search
Zela, A.; Elsken, T.; Saikia, T.; Marrakchi, Y.; Brox, T.; and Hutter, F. 2019 · 1909
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Stabilizing DARTS with Amended Gradient Estimation on Architectural Parameters
Bi, K.; Hu, C.; Xie, L.; Chen, X.; Wei, L.; and Tian, Q. 2019 · 1910
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ImageNet: A large-scale hierarchical image database
Deng, J.; Dong, W.; Socher, R.; Li, L.; Li, K.; and Li, F. 2009 · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A.; and Hinton, G. 2009 · 2009
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Rectified Linear Units Improve Restricted Boltzmann Machines
Nair, V.; and Hinton, G. E. 2010 · 2010
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ImageNet Classification with Deep Convolutional Neural Networks
Krizhevsky, A.; Sutskever, I.; and Hinton, G. E. 2012 · 2012
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Rectifier nonlinearities improve neural network acoustic models
Maas, Andrew L.and Hannun, A. Y.; and Ng, A. Y. 2013 · 2013
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Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2015 · 2015
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Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. 2015 · 2015
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Convolutional Deep Belief Networks on CIFAR-10
Krizhevsky, A. 2015 · 2015
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ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O.; Deng, J.; Su, H.; Krause, J.; Satheesh, S.; Ma, S.; Huang, Z.; Karpathy, A.; Khosla, A.; Bernstein, M. S.; Berg, A. C.; and Li, F. 2015 · 2015
Earlier work this paper cites.
Going deeper with convolutions
Szegedy, C.; Liu, W.; Jia, Y.; Sermanet, P.; Reed, S.; Anguelov, D.; Erhan, D.; Vanhoucke, V.; and Rabinovich, A. 2015 · 2015
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Empirical Evaluation of Rectified Activations in Convolutional Network
Xu, B.; Wang, N.; Chen, T.; and Li, M. 2015 · 2015
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Fast and Accurate Deep Network Learning by Exponential Linear Units(ELUs)
Clevert, D.; Unterthiner, T.; and Hochreiter, S. 2016 · 2016
Cited alongside, same era.
Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
Cited alongside, same era.
Deep Networks with Stochastic Depth
Huang, G.; Sun, Y.; Liu, Z.; Sedra, D.; and Weinberger, K. Q. 2016 · 2016
Cited alongside, same era.
Rethinking the Inception Architecture for Computer Vision
Szegedy, C.; Vanhoucke, V.; Ioffe, S.; Shlens, J.; and Wojna, Z. 2016 · 2016
Cited alongside, same era.
Continuously Differentiable Exponential Linear Units
Barron, J. T. 2017 · 2017
Cited alongside, same era.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
Efficient neural architecture search via parameter sharing
Pham, H.; Guan, M. Y.; Zoph, B.; Le, Q. V.; and Dean, J. 2018 · 2018
Later among the works it cites.
Searching for Activation Functions
Ramachandran, P.; Zoph, B.; and Le, Q. V. 2018 · 2018
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MobileNetV2: Inverted Residuals and Linear Bottlenecks
Sandler, M.; Howard, A. G.; Zhu, M.; Zhmoginov, A.; and Chen, L. 2018 · 2018
Later among the works it cites.
SNAS: stochastic neural architecture search
Xie, S.; Zheng, H.; Liu, C.; and Lin, L. 2018 · 2018
Later among the works it cites.
Learning transferable architectures for scalable image recognition
Zoph, B.; Vasudevan, V.; Shlens, J.; and Le, Q. V. 2018 · 2018
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Howard, A. G.; Zhu, M.; Chen, B.; Kalenichenko, D.; Wang, W.; Weyand, T.; Andreetto, M.; and Adam, H. 2017 · 2017
Cited alongside, same era.
Densely connected convolutional networks
Huang, G.; Liu, Z.; Van Der Maaten, L.; and Weinberger, K. Q. 2017 · 2017
Cited alongside, same era.
Self-Normalizing Neural Networks
Klambauer, G.; an Andreas Mayr, T. U.; and Hochreiter, S. 2017 · 2017
Cited alongside, same era.
FractalNet: Ultra-Deep Neural Networks without Residuals
Larsson, G.; Maire, M.; and Shakhnarovich, G. 2017 · 2017
Cited alongside, same era.
Large-Scale Evolution of Image Classifiers
Real, E.; Moore, S.; Selle, A.; Saxena, S.; Suematsu, Y. L.; Tan, J.; Le, Q. V.; and Kurakin, A. 2017 · 2017
Cited alongside, same era.
Genetic CNN
Xie, L.; and Yuille, A. L. 2017 · 2017
Cited alongside, same era.
Neural Architecture Search with Reinforcement Learning
Zoph, B.; and Le, Q. V. 2017 · 2017
Cited alongside, same era.
Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation
Chen, X.; Xie, L.; Wu, J.; and Tian, Q. 2019 · 2019
Closest in time.
AutoAugment: Learning Augmentation Strategies From Data
Cubuk, E. D.; Zoph, B.; Mane, D.; Vasudevan, V.; and Le, Q. V. 2019 · 2019
Closest in time.
Improved Regularization of Convolutional Neural Networks with Cutout
Devries, T.; and Taylor, G. W. 2019 · 2019
Closest in time.
Searching for a Robust Neural Architecture in Four GPU Hours
Dong, X.; and Yang, Y. 2019 · 2019
Closest in time.
Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution
Elsken, T.; Metzen, J. H.; and Hutter, F. 2019 · 2019
Closest in time.
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection
Ghiasi, G.; Lin, T.; and Le, Q. V. 2019 · 2019
Closest in time.
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
Liu, C.; Chen, L.; Schroff, F.; Adam, H.; Hua, W.; Yuille, A. L.; and Li, F. 2019 · 2019
Closest in time.
DARTS: Differentiable Architecture Search
Liu, H.; Simonyan, K.; and Yang, Y. 2019 · 2019
Closest in time.
Regularized evolution for image classifier architecture search
Real, E.; Aggarwal, A.; Huang, Y.; and Le, Q. V. 2019 · 2019
Closest in time.
Mnasnet: Platform-aware neural architecture search for mobile
Tan, M.; Chen, B.; Pang, R.; Vasudevan, V.; Sandler, M.; Howard, A.; and Le, Q. V. 2019 · 2019
Closest in time.
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Tan, M.; and Le, Q. V. 2019 · 2019
Closest in time.
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search
Wu, B.; Dai, X.; Zhang, P.; Wang, Y.; Sun, F.; Wu, Y.; Tian, Y.; Vajda, P.; Jia, Y.; and Keutzer, K. 2019 · 2019
Closest in time.