Approaches to learning strictly-stable weights for data with missing values

Beliakov, Gleb, Gómez, Daniel, James, Simon, Montero, Javier and Rodríguez, J. Tinguaro 2017, Approaches to learning strictly-stable weights for data with missing values, Fuzzy Sets and Systems, vol. 325, pp. 97-113, doi: 10.1016/j.fss.2017.02.003.

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Title Approaches to learning strictly-stable weights for data with missing values
Author(s) Beliakov, GlebORCID iD for Beliakov, Gleb orcid.org/0000-0002-9841-5292
Gómez, Daniel
James, SimonORCID iD for James, Simon orcid.org/0000-0003-1150-0628
Montero, Javier
Rodríguez, J. Tinguaro
Journal name Fuzzy Sets and Systems
Volume number 325
Start page 97
End page 113
Total pages 17
Publisher Elsevier BV
Place of publication Amsterdam, The Netherlands
Publication date 2017-10-15
ISSN 0165-0114
Keyword(s) aggregation functions
strict stability
missing data
weight learning
linear programming
Science & Technology
Technology
Physical Sciences
Computer Science, Theory & Methods
Mathematics, Applied
Statistics & Probability
Computer Science
Mathematics
OPERATORS
Language eng
DOI 10.1016/j.fss.2017.02.003
Field of Research 0101 Pure Mathematics
0801 Artificial Intelligence And Image Processing
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2017, Elsevier B.V.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30092779

Document type: Journal Article
Collection: School of Information Technology
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