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- aggregation classification "P1".
- aggregation creator person.
- aggregation date "2012".
- aggregation format "application/pdf".
- aggregation hasFormat 3007274.bibtex.
- aggregation hasFormat 3007274.csv.
- aggregation hasFormat 3007274.dc.
- aggregation hasFormat 3007274.didl.
- aggregation hasFormat 3007274.doc.
- aggregation hasFormat 3007274.json.
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- aggregation hasFormat 3007274.yaml.
- aggregation isPartOf urn:isbn:9783642330414.
- aggregation isPartOf urn:issn:2194-5357.
- aggregation language "eng".
- aggregation publisher "Springer".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Mathematics and Statistics".
- aggregation title "The CONEstrip algorithm".
- aggregation abstract "Uncertainty models such as sets of desirable gambles and (conditional) lower previsions can be represented as convex cones. Checking the consistency of and drawing inferences from such models requires solving feasibility and optimization problems. We consider finitely generated such models. For closed cones, we can use linear programming; for conditional lower prevision-based cones, there is an efficient algorithm using an iteration of linear programs. We present an efficient algorithm for general cones that also uses an iteration of linear programs.".
- aggregation authorList BK246661.
- aggregation endPage "54".
- aggregation startPage "45".
- aggregation volume "190".
- aggregation aggregates 3007282.
- aggregation isDescribedBy 3007274.
- aggregation similarTo 978-3-642-33042-1_6.
- aggregation similarTo LU-3007274.