Anti-differentiating approximation algorithms: A case study with min-cuts, spectral, and flow
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David Gleich, Michael W. Mahoney
Anti-differentiating approximation algorithms: A case study with min-cuts, spectral, and flow
ICML, 2014.

ICML c2 2014
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@inproceedings{ICML-c2-2014-GleichM,
	author        = "David Gleich and Michael W. Mahoney",
	booktitle     = "{Proceedings of the 31st International Conference on Machine Learning, Cycle 2}",
	ee            = "http://jmlr.org/proceedings/papers/v32/gleich14.html",
	pages         = "1018--1025",
	publisher     = "{JMLR.org}",
	series        = "{JMLR Proceedings}",
	title         = "{Anti-differentiating approximation algorithms: A case study with min-cuts, spectral, and flow}",
	volume        = 32,
	year          = 2014,
}

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