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Blending multiple convolutional kernels is proved advantageous in neural architecture design.
A New Measure of Rank Correlation
Maurice G Kendall · 1938
Earlier work this paper cites.
A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II
Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and TAMT Meyarivan · 2002
Earlier work this paper cites.
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Laurens Van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
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Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Learning Multiple Layers of Features from Tiny Images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
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Tsung-Yi Lin, Michael Maire, Serge J. Belongie, Lubomir D. Bourdev, Ross B. Girshick, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
Earlier work this paper cites.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe and Christian Szegedy · 2015
Earlier work this paper cites.
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Earlier work this paper cites.
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Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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