Optimal training of integer-valued neural networks with mixed integer programming

Recent work has shown potential in using Mixed Integer Programming (MIP) solvers to optimize certain aspects of neural networks (NNs). However the intriguing approach of training NNs with MIP solvers is under-explored. State-of-the-art-methods to train NNs are typically gradient-based and require si...

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Veröffentlicht in:	PloS one Jg. 18; H. 2; S. e0261029
Hauptverfasser:	Thorbjarnarson, Tómas, Yorke-Smith, Neil
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 01.02.2023 Public Library of Science (PLoS)
Schlagworte:	Analysis Biology and Life Sciences Computer and Information Sciences Computer architecture Graphics processing units Integer programming Linear programming Mathematical models Medicine and Health Sciences Memory (Computers) Memory devices Mixed integer Network management systems Neural networks Neurons Optimization Parameters Physical Sciences Solvers Training Tuning Netherlands
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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