Strong mixed-integer programming formulations for trained neural networks

We present strong mixed-integer programming (MIP) formulations for high-dimensional piecewise linear functions that correspond to trained neural networks. These formulations can be used for a number of important tasks, such as verifying that an image classification network is robust to adversarial i...

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Vydáno v:	Mathematical programming Ročník 183; číslo 1-2; s. 3 - 39
Hlavní autoři:	Anderson, Ross, Huchette, Joey, Ma, Will, Tjandraatmadja, Christian, Vielma, Juan Pablo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020 Springer Nature B.V
Témata:	Calculus of Variations and Optimal Control; Optimization Combinatorics Full Length Paper Image classification Integer programming Linear functions Linear programming Machine learning Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Mathematics of Computing Mixed integer Neural networks Numerical Analysis Theoretical Formulations Deep learning Mixed-integer programming 90C11
ISSN:	0025-5610, 1436-4646
On-line přístup:	Získat plný text
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