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Deep Neural Networks (DNNs) are very popular these days, and are the subject of a very intense investigation.
Gradient-based learning applied to document recognition
Y. L. Le Cun, L. Bottou, Y. Bengio, and P. Haffner · 1998
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Local branching
M. Fischetti and A. Lodi · 2003
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An evolutionary algorithm for polishing mixed integer programming solutions
E. Rothberg · 2007
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Visualizing higher-layer features of a deep network, 2009
D. Erhan, Y. Bengio, A. Courville, and P. Vincent · 2009
Earlier work this paper cites.
Rectified linear units improve restricted boltzmann machines
V. Nair and G.E. Hinton · 2010
Cited alongside, same era.
Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I.J. Goodfellow, and R. Fergus · 2013
Cited alongside, same era.
Fast training of support vector machines with gaussian kernel
M. Fischetti · 2014
Cited alongside, same era.
Proximity search for 0-1 mixed-integer convex programming
M. Fischetti and M. Monaci · 2014
Cited alongside, same era.
On handling indicator constraints in mixed integer programming
P. Belotti, P. Bonami, M. Fischetti, A. Lodi, M. Monaci, A. Nogales-Gomez, and D. Salvagnin · 2016
Later among the works it cites.
Cplex 12.7 user’s manual, 2017
ILOG IBM · 2017
Closest in time.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G.E. Hinton · 2017
Closest in time.
Bounding and counting linear regions of deep neural networks
T. Serra, C. Tjandraatmadja, and S. Ramalingam · 2017
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