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Structured Prediction Problem Archive

MPS-Authors
/persons/resource/persons221924

Swoboda,  Paul
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;

/persons/resource/persons180806

Horňáková,  Andrea
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;

/persons/resource/persons285142

Rötzer,  Paul
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;

/persons/resource/persons238023

Abbas,  Ahmed
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;

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arXiv:2202.03574.pdf
(Preprint), 3MB

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Citation

Swoboda, P., Horňáková, A., Rötzer, P., Savchynskyy, B., & Abbas, A. (2022). Structured Prediction Problem Archive. Retrieved from https://arxiv.org/abs/2202.03574.


Cite as: https://hdl.handle.net/21.11116/0000-000C-2AAA-6
Abstract
Structured prediction problems are one of the fundamental tools in machine
learning. In order to facilitate algorithm development for their numerical
solution, we collect in one place a large number of datasets in easy to read
formats for a diverse set of problem classes. We provide archival links to
datasets, description of the considered problems and problem formats, and a
short summary of problem characteristics including size, number of instances
etc. For reference we also give a non-exhaustive selection of algorithms
proposed in the literature for their solution. We hope that this central
repository will make benchmarking and comparison to established works easier.
We welcome submission of interesting new datasets and algorithms for inclusion
in our archive.