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Runtime Optimizations for Tree-Based Machine Learning Models

contributor authorAsadi, Nima
contributor authorLin, James
contributor authorde Vries, Arjen P.
date accessioned2020-03-12T18:23:10Z
date available2020-03-12T18:23:10Z
date issued2014
identifier issn1041-4347
identifier other6513227.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/956718?show=full
formatgeneral
languageEnglish
publisherIEEE
titleRuntime Optimizations for Tree-Based Machine Learning Models
typeJournal Paper
contenttypeMetadata Only
identifier padid7988822
subject keywordsInternet
subject keywordscache storage
subject keywordsinformation retrieval
subject keywordslearning (artificial intelligence)
subject keywordsregression analysis
subject keywordstree data structures
subject keywordsWeb ranking
subject keywordscache-conscious fashion
subject keywordsdata structures
subject keywordsexecution flow
subject keywordsgradient-boosted regression trees
subject keywordslearning-to-rank datasets
subject keywordsmicrobatching predictions
subject keywordspredication technique
subject keywordsprocessor architectures
subject keywordsruntime performance optimizations
subject keywordssuperscalar processors
subject keywordssynthetic data
subject keywordstree-based machine learning models
subject keywordsvectorization technique
subject keywordsArrays
subject keywordsIndexes
subject keywordsOptimization
identifier doi10.1109/TKDE.2013.73
journal titleKnowledge and Data Engineering, IEEE Transactions on
journal volume26
journal issue9
filesize1037529
citations0


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