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We develop an approach to growing deep network architectures over the course of training, driven by a principled combination of accuracy and sparsity objectives.
Building a large annotated corpus of english: The penn treebank
Mitchell P. Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz · 1993
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Long short-term memory
Sepp Hochreiter and Jurgen Schmidhuber · 1997
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ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Semantic contours from inverse detectors
Bharath Hariharan, Pablo Arbelaez, Lubomir D. Bourdev, Subhransu Maji, and Jitendra Malik · 2011
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ImageNet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Min Lin, Qiang Chen, and Shuicheng Yan · 2013
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Learning phrase representations using RNN encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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The CIFAR-10 dataset
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton · 2014
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Rigid-motion scattering for image classification
Laurent Sifre and PS Mallat · 2014
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Recurrent neural network regularization
Wojciech Zaremba, Ilya Sutskever, and Oriol Vinyals · 2014
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The PASCAL visual object classes challenge: A retrospective
Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John M. Winn, and Andrew Zisserman · 2015
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Fast R-CNN
Ross B. Girshick · 2015
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Learning both weights and connections for efficient neural networks
Song Han, Jeff Pool, John Tran, and William J. Dally · 2015
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Distilling the knowledge in a neural network
Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Training and investigating residual nets
Sam Gross and Michael Wilber · 2016
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Dynamic network surgery for efficient DNNs
Yiwen Guo, Anbang Yao, and Yurong Chen · 2016
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Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding
Song Han, Huizi Mao, and William J. Dally · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deep networks with stochastic depth
Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, and Kilian Q. Weinberger · 2016
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Binarized neural networks
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio · 2016
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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size
Forrest N. Iandola, Matthew W. Moskewicz, Khalid Ashraf, Song Han, William J. Dally, and Kurt Keutzer · 2016
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SSD: single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, and Alexander C. Berg · 2016
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XNOR-Net: Imagenet classification using binary convolutional neural networks
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Farhadi · 2016
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Network morphism
Tao Wei, Changhu Wang, Yong Rui, and Chang Wen Chen · 2016
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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
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Hashnet: Deep learning to hash by continuation
Zhangjie Cao, Mingsheng Long, Jianmin Wang, and Philip S. Yu · 2017
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
Learning intrinsic sparse structures within long short-term memory
Wei Wen, Yuxiong He, Samyam Rajbhandari, Minjia Zhang, Wenhan Wang, Fang Liu, Bin Hu, Yiran Chen, and Hai Li · 2018
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NetAdapt: Platform-aware neural network adaptation for mobile applications
Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, and Hartwig Adam · 2018
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ShuffleNet: An extremely efficient convolutional neural network for mobile devices
Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, and Jian Sun · 2018
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Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le · 2018
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Proxylessnas: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2019
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
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Accurate, large minibatch SGD: training imagenet in 1 hour
Priya Goyal, Piotr Dollár, Ross B. Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q. Weinberger · 2017
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
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Pruning filters for efficient ConvNets
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf · 2017
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Ekin Dogus Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, and Quoc V. Le · 2019
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin · 2019
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Structured pruning of neural networks with budget-aware regularization
Carl Lemaire, Andrew Achkar, and Pierre-Marc Jodoin · 2019
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Random search and reproducibility for neural architecture search
Liam Li and Ameet Talwalkar · 2019
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Darts: Differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2019
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On network design spaces for visual recognition
Ilija Radosavovic, Justin Johnson, Saining Xie, Wan-Yen Lo, and Piotr Dollár · 2019
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Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V. Le · 2019
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Learning implicitly recurrent CNNs through parameter sharing
Pedro Savarese and Michael Maire · 2019
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Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc V. Le · 2019
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Mnasnet: Platform-aware neural architecture search for mobile
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, and Quoc V Le · 2019
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Discovering neural wirings
Mitchell Wortsman, Ali Farhadi, and Mohammad Rastegari · 2019
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Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, and Kurt Keutzer · 2019
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Provable filter pruning for efficient neural networks
Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, and Daniela Rus · 2020
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Winning the lottery with continuous sparsification
Pedro Savarese, Hugo Silva, and Michael Maire · 2020
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Autogrow: Automatic layer growing in deep convolutional networks
Wei Wen, Feng Yan, Yiran Chen, and Hai Li · 2020
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Spatially adaptive inference with stochastic feature sampling and interpolation
Zhenda Xie, Zheng Zhang, Xizhou Zhu, Gao Huang, and Stephen Lin · 2020
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Evaluating the search phase of neural architecture search
Kaicheng Yu, Christian Sciuto, Martin Jaggi, Claudiu Musat, and Mathieu Salzmann · 2020
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