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Mathematics / Combinatorial optimization / Cutting-plane method / Numerical software / Linear programming relaxation / SCIP / Bayesian network / Linear programming / Mathematical optimization / Operations research / Numerical analysis


Bayesian network learning with cutting planes James Cussens Dept of Computer Science & York Centre for Complex Systems Analysis University of York, Deramore Lane, York, YO10 5GH, UK
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Document Date: 2011-09-21 23:06:45

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City

Helsinki / Edinburgh / /

Company

AUAI Press / MIT Press / /

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Facility

Complex Systems Analysis University of York / /

IndustryTerm

simplex algorithm / heuristic search / branch-andcut search / plane algorithm / suboptimal solutions / search approach / incumbent solutions / feasible integer solution / incumbent solution / search-based model averaging approach / learning algorithm / integral solution / pre-processing algorithms / search-and-score / search methods / /

OperatingSystem

UNIX / Linux / /

Organization

University of York / MIT / WCB / Computer Science & York Centre / /

Person

David Maxwell Chickering / Amir Globerson / Michael Winkler / Tommi Jaakkola / Ambros Gleixner / Ronald L. Rivest / Christopher Meek / Stefan Heinz / Kati Wolter / Mikko Koivisto / L. van der Gaag / Tomi Silander / Timo Berthold / James Cussens / Laurence A. Wolsey / Robert G. Cowell / Tobias Achterberg / David Heckerman / David Sontag / Charles E. Leiserson / John Wiley / Thomas H. Cormen / Marina Meila / Ricardo Silva / Petri Myllym¨aki / Kismat Sood / /

Position

author / /

ProgrammingLanguage

Python / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

RadioStation

Core / /

Technology

RAM / Bioinformatics / artificial intelligence / cutting plane algorithm / Linux / UNIX / pre-processing algorithms / simplex algorithm / Machine Learning / html / /

URL

http /

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