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We present an approach to adaptively utilize deep neural networks in order to reduce the evaluation time on new examples without loss of accuracy.
Model compression
Bucila, Cristian, Caruana, Rich, and Niculescu-Mizil, Alexandru · 2006
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Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
Hinton, Geoffrey, Deng, Li, Yu, Dong, Dahl, George E, Mohamed, Abdel-rahman, Jaitly, Navdeep, Senior, Andrew, Vanhoucke, Vincent, Nguyen, Patrick, Sainath, Tara N, et al · 2012
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Imagenet classification with deep convolutional neural networks
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoffrey E · 2012
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Local supervised learning through space partitioning
Wang, Joseph and Saligrama, Venkatesh · 2012
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Supervised sequential classification under budget constraints
Trapeznikov, K and Saligrama, V · 2013
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Cost-sensitive tree of classifiers
Xu, Z., Kusner, M., Chen, M., and Weinberger, K · 2013
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Compressing deep convolutional networks using vector quantization
Gong, Yunchao, Liu, Liu, Yang, Ming, and Bourdev, Lubomir · 2014
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Feature-cost sensitive learning with submodular trees of classifiers
Kusner, M, Chen, W, Zhou, Q, Xu, Z, Weinberger, K, and Chen, Y · 2014
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Sequence to sequence learning with neural networks
Sutskever, Ilya, Vinyals, Oriol, and Le, Quoc V · 2014
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Model selection by linear programming
Wang, J., Bolukbasi, T., Trapeznikov, K., and Saligrama, V · 2014
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Conditional computation in neural networks for faster models
Bengio, Emmanuel, Bacon, Pierre-Luc, Pineau, Joelle, and Precup, Doina · 2015
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Compressing neural networks with the hashing trick
Chen, Wenlin, Wilson, James T, Tyree, Stephen, Weinberger, Kilian Q, and Chen, Yixin · 2015
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Binaryconnect: Training deep neural networks with binary weights during propagations
Courbariaux, Matthieu, Bengio, Yoshua, and David, Jean-Pierre · 2015
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Distilling the knowledge in a neural network
Hinton, Geoffrey, Vinyals, Oriol, and Dean, Jeff · 2015
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Lcnn: Lookup-based convolutional neural network
Bagherinezhad, Hessam, Rastegari, Mohammad, and Farhadi, Ali · 2016
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Deep residual learning for image recognition
He, Kaiming, Zhang, Xiangyu, Ren, Shaoqing, and Sun, Jian · 2016
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Squeezenet: Alexnet-level accuracy with 50x fewer parameters and< 0.5 mb model size
Iandola, Forrest N, Han, Song, Moskewicz, Matthew W, Ashraf, Khalid, Dally, William J, and Keutzer, Kurt · 2016
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Pruning random forests for prediction on a budget
Nan, Feng, Wang, Joseph, and Saligrama, Venkatesh · 2016
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Xnor-net: Imagenet classification using binary convolutional neural networks
Rastegari, Mohammad, Ordonez, Vicente, Redmon, Joseph, and Farhadi, Ali · 2016
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Sparse convolutional neural networks
Liu, Baoyuan, Wang, Min, Foroosh, Hassan, Tappen, Marshall, and Pensky, Marianna · 2015
Cited alongside, same era.
Imagenet large scale visual recognition challenge
Russakovsky, Olga, Deng, Jia, Su, Hao, Krause, Jonathan, Satheesh, Sanjeev, Ma, Sean, Huang, Zhiheng, Karpathy, Andrej, Khosla, Aditya, Bernstein, Michael, et al · 2015
Cited alongside, same era.
Going deeper with convolutions
Szegedy, Christian, Liu, Wei, Jia, Yangqing, Sermanet, Pierre, Reed, Scott, Anguelov, Dragomir, Erhan, Dumitru, Vanhoucke, Vincent, and Rabinovich, Andrew · 2015
Cited alongside, same era.
Efficient learning by directed acyclic graph for resource constrained prediction
Wang, Joseph, Trapeznikov, Kirill, and Saligrama, Venkatesh · 2015
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Spatially adaptive computation time for residual networks
Figurnov, Michael, Collins, Maxwell D, Zhu, Yukun, Zhang, Li, Huang, Jonathan, Vetrov, Dmitry, and Salakhutdinov, Ruslan
Cited in the paper.
Perforatedcnns: Acceleration through elimination of redundant convolutions
Figurnov, Mikhail, Ibraimova, Aizhan, Vetrov, Dmitry P, and Kohli, Pushmeet
Cited in the paper.
Binarized neural networks
Hubara, Itay, Courbariaux, Matthieu, Soudry, Daniel, El-Yaniv, Ran, and Bengio, Yoshua
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Learning structured sparsity in deep neural networks
Wen, Wei, Wu, Chunpeng, Wang, Yandan, Chen, Yiran, and Li, Hai · 2016
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Quantized convolutional neural networks for mobile devices
Wu, Jiaxiang, Leng, Cong, Wang, Yuhang, Hu, Qinghao, and Cheng, Jian · 2016
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The cascading neural network: building the internet of smart things
Leroux, Sam, Bohez, Steven, De Coninck, Elias, Verbelen, Tim, Vankeirsbilck, Bert, Simoens, Pieter, and Dhoedt, Bart · 2017
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Changing model behavior at test-time using reinforcement learning
Odena, Augustus, Lawson, Dieterich, and Olah, Christopher · 2017
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