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Model binarization can significantly compress model size, reduce energy consumption, and accelerate inference through efficient bit-wise operations.
Efficient sparse coding algorithms
Honglak Lee, Alexis Battle, Rajat Raina, and Andrew Ng · 2006
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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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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
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cudnn: Efficient primitives for deep learning
Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, and Evan Shelhamer · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Distilling the knowledge in a neural network
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Binarynet: Training deep neural networks with weights and activations constrained to +1 or -1
Matthieu Courbariaux and Yoshua Bengio · 2016
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Matthieu Courbariaux, Itay Hubara, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio · 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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Fast algorithms for convolutional neural networks
Andrew Lavin and Scott Gray · 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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Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
Shuchang Zhou, Yuxin Wu, Zekun Ni, Xinyu Zhou, He Wen, and Yuheng Zou · 2016
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Loss-aware binarization of deep networks
Lu Hou, Quanming Yao, and James Tin Yau Kwok · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Tiny imagenet challenge
Jiayu Wu, Qixiang Zhang, and Guoxi Xu · 2017
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Proxquant: Quantized neural networks via proximal operators
Yu Bai, Yu-Xiang Wang, and Edo Liberty · 2018
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Efficient sparse-winograd convolutional neural networks
Xingyu Liu, Jeff Pool, Song Han, and William J Dally · 2018
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Bi-real net: Enhancing the performance of 1-bit cnns with improved representational capability and advanced training algorithm
Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, and Kwang-Ting Cheng · 2018
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Apprentice: Using knowledge distillation techniques to improve low-precision network accuracy
Asit Mishra and Debbie Marr · 2018
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Wrpn: Wide reduced-precision networks
Asit Mishra, Eriko Nurvitadhi, Jeffrey J Cook, and Debbie Marr · 2018
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Lq-nets: Learned quantization for highly accurate and compact deep neural networks
Dongqing Zhang, Jiaolong Yang, Dongqiangzi Ye, and Gang Hua · 2018
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Towards effective low-bitwidth convolutional neural networks
Bohan Zhuang, Chunhua Shen, Mingkui Tan, Lingqiao Liu, and Ian Reid · 2018
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A systematic study of binary neural networks’ optimisation
Milad Alizadeh, Javier Fernández-Marqués, Nicholas D Lane, and Yarin Gal · 2019
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Xnor-net++: Improved binary neural networks
Adrian Bulat and Georgios Tzimiropoulos · 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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Circulant binary convolutional networks: Enhancing the performance of 1-bit dcnns with circulant back propagation
Chunlei Liu, Wenrui Ding, Xin Xia, Baochang Zhang, Jiaxin Gu, Jianzhuang Liu, Rongrong Ji, and David Doermann · 2019
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Training binary neural networks with real-to-binary convolutions
Brais Martinez, Jing Yang, Adrian Bulat, and Georgios Tzimiropoulos · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Pytorch image models
Ross Wightman · 2019
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Binary ensemble neural network: More bits per network or more networks per bit?
Shilin Zhu, Xin Dong, and Hao Su · 2019
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High-capacity expert binary networks
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Herve Jegou · 2021
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Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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Nvit: Vision transformer compression and parameter redistribution
Huanrui Yang, Hongxu Yin, Pavlo Molchanov, Hai Li, and Jan Kautz · 2021
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A unified pruning framework for vision transformers
Hao Yu and Jianxin Wu · 2021
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Adrian Bulat, Brais Martinez, and Georgios Tzimiropoulos · 2020
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Reactnet: Towards precise binary neural network with generalized activation functions
Zechun Liu, Zhiqiang Shen, Marios Savvides, and Kwang-Ting Cheng · 2020
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Forward and backward information retention for accurate binary neural networks
Haotong Qin, Ruihao Gong, Xianglong Liu, Mingzhu Shen, Ziran Wei, Fengwei Yu, and Jingkuan Song · 2020
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Binary graph neural networks
Mehdi Bahri, Gaétan Bahl, and Stefanos Zafeiriou · 2021
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Binarybert: Pushing the limit of bert quantization
Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jin Jin, Xin Jiang, Qun Liu, Michael R Lyu, and Irwin King · 2021
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Ptq4vit: Post-training quantization framework for vision transformers
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Improving visual quality of image synthesis by a token-based generator with transformers
Yanhong Zeng, Huan Yang, Hongyang Chao, Jianbo Wang, and Jianlong Fu · 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip HS Torr, et al · 2021
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Mingjian Zhu, Yehui Tang, and Kai Han · 2021
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Efficientvit: Enhanced linear attention for high-resolution low-computation visual recognition
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Multi-dimensional vision transformer compression via dependency guided gaussian process search
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