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Designing effective architectures is one of the key factors behind the success of deep neural networks.
Backpropagation Applied to Handwritten zip Code Recognition
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. J. Williams · 1992
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Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky and G. Hinton · 2009
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Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Network in network
M. Lin, Q. Chen, and S. Yan · 2014
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Towards ultrahigh dimensional feature selection for big data
M. Tan, I. W. Tsang, and L. Wang · 2014
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Topic modeling of multimodal data: An autoregressive approach
Y. Zheng, Y.-J. Zhang, and H. Larochelle · 2014
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Facenet: A Unified Embedding for Face Recognition and Clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
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Trust region policy optimization
J. Schulman, S. Levine, P. Abbeel, M. Jordan, and P. Moritz · 2015
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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Training Very Deep Networks
R. K. Srivastava, K. Greff, and J. Schmidhuber · 2015
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Deeply Learned Face Representations are Sparse, Selective, and Robust
Y. Sun, X. Wang, and X. Tang · 2015
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A neural autoregressive approach to attention-based recognition
Y. Zheng, R. S. Zemel, Y.-J. Zhang, and H. Larochelle · 2015
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A deep and autoregressive approach for topic modeling of multimodal data
Y. Zheng, Y.-J. Zhang, and H. Larochelle · 2015
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Net2net: Accelerating learning via knowledge transfer
T. Chen, I. Goodfellow, and J. Shlens · 2016
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The shallow end: Empowering shallower deep-convolutional networks through auxiliary outputs
Y. Guo, M. Tan, Q. Wu, J. Chen, A. V. D. Hengel, and Q. Shi · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Identity mappings in deep residual networks
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2016
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An eeg-based brain-computer interface for emotion recognition
J. Pan, Y. Li, and J. Wang · 2016
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Neural autoregressive collaborative filtering for implicit feedback
Y. Zheng, C. Liu, B. Tang, and H. Zhou · 2016
Cited alongside, same era.
A neural autoregressive approach to collaborative filtering
Y. Zheng, B. Tang, W. Ding, and H. Zhou · 2016
Cited alongside, same era.
Designing neural network architectures using reinforcement learning
B. Baker, O. Gupta, N. Naik, and R. Raskar · 2017
Cited alongside, same era.
Channel pruning for accelerating very deep neural networks
Y. He, X. Zhang, and J. Sun · 2017
Cited alongside, same era.
Mobilenetv2: Inverted residuals and linear bottlenecks
M. Sandler, A. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen · 2018
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Netadapt: Platform-aware neural network adaptation for mobile applications
T.-J. Yang, A. Howard, B. Chen, X. Zhang, A. Go, M. Sandler, V. Sze, and H. Adam · 2018
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You only search once: Single shot neural architecture search via direct sparse optimization
X. Zhang, Z. Huang, and N. Wang · 2018
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Practical block-wise neural network architecture generation
Z. Zhong, J. Yan, W. Wu, J. Shao, and C.-L. Liu · 2018
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Discrimination-aware channel pruning for deep neural networks
Z. Zhuang, M. Tan, B. Zhuang, J. Liu, Y. Guo, Q. Wu, J. Huang, and J. Zhu · 2018
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Variational deep embedding: An unsupervised and generative approach to clustering
Z. Jiang, Y. Zheng, H. Tan, B. Tang, and H. Zhou · 2017
Cited alongside, same era.
Document neural autoregressive distribution estimation
S. Lauly, Y. Zheng, A. Allauzen, and H. Larochelle · 2017
Cited alongside, same era.
Pruning filters for efficient convnets
H. Li, A. Kadav, I. Durdanovic, H. Samet, and H. P. Graf · 2017
Cited alongside, same era.
Thinet: A filter level pruning method for deep neural network compression
J.-H. Luo, J. Wu, and W. Lin · 2017
Cited alongside, same era.
Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
Cited alongside, same era.
Neural architecture search with reinforcement learning
B. Zoph and Q. V. Le · 2017
Cited alongside, same era.
B. Zoph, V. Vasudevan, J. Shlens, and Q. V. Le · 2018
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ProxylessNAS: Direct neural architecture search on target task and hardware
H. Cai, L. Zhu, and S. Han · 2019
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Multi-marginal wasserstein gan
J. Cao, L. Mo, Y. Zhang, K. Jia, C. Shen, and M. Tan · 2019
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Learnable embedding space for efficient neural architecture compression
S. Cao, X. Wang, and K. M. Kitani · 2019
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Chamnet: Towards efficient network design through platform-aware model adaptation
X. Dai, P. Zhang, B. Wu, H. Yin, F. Sun, Y. Wang, M. Dukhan, Y. Hu, Y. Wu, Y. Jia, et al · 2019
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Auto-embedding generative adversarial networks for high resolution image synthesis
Y. Guo, Q. Chen, J. Chen, Q. Wu, Q. Shi, and M. Tan · 2019
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Learning multimodal graph-to-graph translation for molecular optimization
W. Jin, K. Yang, R. Barzilay, and T. Jaakkola · 2019
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Darts: Differentiable architecture search
H. Liu, K. Simonyan, and Y. Yang · 2019
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Regularized evolution for image classifier architecture search
E. Real, A. Aggarwal, Y. Huang, and Q. V. Le · 2019
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The evolved transformer
D. R. So, C. Liang, and Q. V. Le · 2019
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Snas: Stochastic neural architecture search
S. Xie, H. Zheng, C. Liu, and L. Lin · 2019
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Breaking winner-takes-all: Iterative-winners-out networks for weakly supervised temporal action localization
R. Zeng, C. Gan, P. Chen, W. Huang, Q. Wu, and M. Tan · 2019
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Graph convolutional networks for temporal action localization
R. Zeng, W. Huang, M. Tan, Y. Rong, P. Zhao, J. Huang, and C. Gan · 2019
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Graph hypernetworks for neural architecture search
C. Zhang, M. Ren, and R. Urtasun · 2019
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From whole slide imaging to microscopy: Deep microscopy adaptation network for histopathology cancer image classification
Y. Zhang, H. Chen, Y. Wei, P. Zhao, J. Cao, X. Fan, X. Lou, H. Liu, J. Hou, X. Han, et al · 2019
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