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Graphical model parameter learning by inverse linear programming

We introduce two novel methods for learning parameters of graphical models for image labelling. The following two tasks underline both methods: (i) perturb model parameters based on given features and ground truth labelings, so as to exactly reproduce these labelings as optima of the local polytope...

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Main Authors: Trajkovska, Vera (Author) , Swoboda, Paul (Author) , Åström, Freddie (Author) , Petra, Stefania (Author)
Format: Chapter/Article Conference Paper
Language:English
Published: 18 May 2017
In: Scale Space and Variational Methods in Computer Vision
Year: 2017, Pages: 323-334
DOI:10.1007/978-3-319-58771-4_26
Subjects:
Konferenzschrift
Online Access:Verlag, Volltext: http://dx.doi.org/10.1007/978-3-319-58771-4_26
Verlag, Volltext: https://link.springer.com/chapter/10.1007/978-3-319-58771-4_26
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Author Notes:Vera Trajkovska, Paul Swoboda, Freddie Åström, Stefania Petra

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