Show simple item record

A Gaussian Process Model for Data Association and a Semidefinite Programming Solution

contributor authorLazaro-Gredilla, Miguel
contributor authorVan Vaerenbergh, Steven
date accessioned2020-03-12T18:44:42Z
date available2020-03-12T18:44:42Z
date issued2014
identifier issn2162-237X
identifier other6730932.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/968667?show=full
formatgeneral
languageEnglish
publisherIEEE
titleA Gaussian Process Model for Data Association and a Semidefinite Programming Solution
typeJournal Paper
contenttypeMetadata Only
identifier padid8002827
subject keywordsGaussian processes
subject keywordsmathematical programming
subject keywordspattern clustering
subject keywordssensor fusion
subject keywordstarget tracking
subject keywordsBayesian model
subject keywordsGaussian process model
subject keywordsMaxCut problem
subject keywordsSDP relaxation
subject keywordsconstrained Max K-section problem
subject keywordsdata association problem
subject keywordshyperparameters
subject keywordsoptimization problem
subject keywordssemidefinite programming solution
subject keywordstrajectory smoothness
subject keywordsBayes methods
subject keywordsData models
subject keywordsOptimization
subject keywordsResource management
subject keywordsStandards
subject keywordsTrajectory
subject keywordsVectors
subject keywordsClustering
subject keywordsGaussian processes (GPs)
subject keywordsdata association
subject keywordsmultitarget tracking
identifier doi10.1109/TNNLS.2014.2300701
journal titleNeural Networks and Learning Systems, IEEE Transactions on
journal volume25
journal issue11
filesize1286322
citations0


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record