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We introduce a learning-based framework to optimize tensor programs for deep learning workloads.
An analysis of approximations for maximizing submodular set functions—i
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Optiml: An implicitly parallel domain-specific language for machine learning
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Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, and Yoshua Bengio · 2012
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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Jasper Snoek, Hugo Larochelle, and Ryan P. Adams · 2012
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Jonathan Ragan-Kelley, Connelly Barnes, Andrew Adams, Sylvain Paris, Frédo Durand, and Saman Amarasinghe · 2013
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Sven Verdoolaege, Juan Carlos Juega, Albert Cohen, José Ignacio Gómez, Christian Tenllado, and Francky Catthoor · 2013
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An introduction to computational networks and the computational network toolkit
Amit Agarwal, Eldar Akchurin, Chris Basoglu, Guoguo Chen, Scott Cyphers, Jasha Droppo, Adam Eversole, Brian Guenter, Mark Hillebrand, Ryan Hoens, Xuedong Huang, Zhiheng Huang, Vladimir Ivanov, Alexey Kamenev, Philipp Kranen, Oleksii Kuchaiev, Wolfgang Manousek, Avner May, Bhaskar Mitra, Olivier Nano, Gaizka Navarro, Alexey Orlov, Marko Padmilac, Hari Parthasarathi, Baolin Peng, Alexey Reznichenko, Frank Seide, Michael L. Seltzer, Malcolm Slaney, Andreas Stolcke, Yongqiang Wang, Huaming Wang, Kaisheng Yao, Dong Yu, Yu Zhang, and Geoffrey Zweig · 2014
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Submodular function maximization
Andreas Krause and Daniel Golovin · 2014
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Ilya Sutskever, Oriol Vinyals, and Quoc V. Le · 2014
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Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, , and Zheng Zhang · 2015
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Algorithm runtime prediction: Methods and evaluation (extended abstract)
Frank Hutter, Lin Xu, Holger Hoos, and Kevin Leyton-Brown · 2015
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Human-level control through deep reinforcement learning
Automatically scheduling halide image processing pipelines
Ravi Teja Mullapudi, Andrew Adams, Dillon Sharlet, Jonathan Ragan-Kelley, and Kayvon Fatahalian · 2016
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Taking the human out of the loop: A review of bayesian optimization
B. Shahriari, K. Swersky, Z. Wang, R. P. Adams, and N. de Freitas · 2016
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Google vizier: A service for black-box optimization
Daniel Golovin, Benjamin Solnik, Subhodeep Moitra, Greg Kochanski, John Karro, and D. Sculley · 2017
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Futhark: Purely functional gpu-programming with nested parallelism and in-place array updates
Troels Henriksen, Niels G. W. Serup, Martin Elsman, Fritz Henglein, and Cosmin E. Oancea · 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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Kai Sheng Tai, Richard Socher, and Christopher D Manning · 2015
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The case for learned index structures
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Tensor comprehensions: Framework-agnostic high-performance machine learning abstractions
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