Efficient techniques for simultaneous variable selection and sensor selection via convex selection inducing penalties

Show simple item record

dc.contributor.author Fokoue, Ernest
dc.date.accessioned 2011-01-04T14:29:56Z
dc.date.available 2011-01-04T14:29:56Z
dc.date.issued 2011-01-03
dc.identifier.uri http://hdl.handle.net/1850/13086
dc.description.abstract This paper extends results from the traditional D-optimality machinery to derive an efficient technique for simultaneous variable selection and sensor selection. An important advantage of the proposed technique is the convexity of the formulated optimization task along with a byproduct of straightforward sparsity. The theoretical foundation of the proposed method is explored at great length, and a variety of examples are provided to demonstrated the effectiveness of our technique. Comparisons with existing techniques are offered that provide evidence as the superiority of our technique on a variety of indicators. en_US
dc.language.iso en_US en_US
dc.subject Bayesian analysis en_US
dc.subject Convex optimization en_US
dc.subject D-Optimality en_US
dc.subject Optimal experimental design en_US
dc.subject Sensor selection en_US
dc.subject Sparsity en_US
dc.subject Variable selection en_US
dc.title Efficient techniques for simultaneous variable selection and sensor selection via convex selection inducing penalties en_US
dc.type Article en_US

Files in this item

Files Size Format View
EFokoueArticle01-03-2011.pdf 162.6Kb PDF View/Open

This item appears in the following Collection(s)

Show simple item record

Search RIT DML


Advanced Search

Browse