Matches in SemOpenAlex for { <https://semopenalex.org/work/W1531909365> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W1531909365 abstract "Previous chapter Next chapter Full AccessProceedings Proceedings of the 2008 SIAM International Conference on Data Mining (SDM)Active Learning with Model Selection in Linear RegressionMasashi Sugiyama and Neil RubensMasashi SugiyamaDepartment of Computer Science, Tokyo Institute of Technology, Tokyo, Japan.Department of Computer Science, Tokyo Institute of Technology, Tokyo, Japan.Search for more papers by this author and Neil RubensDepartment of Computer Science, Tokyo Institute of Technology, Tokyo, Japan.Department of Computer Science, Tokyo Institute of Technology, Tokyo, Japan.Search for more papers by this authorpp.518 - 529Chapter DOI:https://doi.org/10.1137/1.9781611972788.47PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and have been studied extensively. However, these two issues seem to have been investigated separately as two independent problems. If training input points and models are simultaneously optimized, the generalization performance would be further improved. In this paper, we propose a new approach called ensemble active learning for solving the problems of active learning and model selection at the same time. We demonstrate by numerical experiments that the proposed method compares favorably with alternative approaches such as iteratively performing active learning and model selection in a sequential manner. Previous chapter Next chapter RelatedDetails Published:2008ISBN:978-0-89871-654-2eISBN:978-1-61197-278-8 https://doi.org/10.1137/1.9781611972788Book Series Name:ProceedingsBook Code:PR130Book Pages:1-869" @default.
- W1531909365 created "2016-06-24" @default.
- W1531909365 creator A5071708239 @default.
- W1531909365 creator A5072744508 @default.
- W1531909365 date "2008-04-24" @default.
- W1531909365 modified "2023-09-25" @default.
- W1531909365 title "Active Learning with Model Selection in Linear Regression" @default.
- W1531909365 cites W1603576850 @default.
- W1531909365 cites W189742998 @default.
- W1531909365 cites W1963661053 @default.
- W1531909365 cites W2032536435 @default.
- W1531909365 cites W2034368206 @default.
- W1531909365 cites W2054658115 @default.
- W1531909365 cites W2081850149 @default.
- W1531909365 cites W2086674778 @default.
- W1531909365 cites W2109033052 @default.
- W1531909365 cites W2112483442 @default.
- W1531909365 cites W2114338449 @default.
- W1531909365 cites W2115305054 @default.
- W1531909365 cites W2140170995 @default.
- W1531909365 cites W2142635246 @default.
- W1531909365 cites W2144578442 @default.
- W1531909365 cites W2148924730 @default.
- W1531909365 cites W2168175751 @default.
- W1531909365 cites W2218277484 @default.
- W1531909365 cites W2255883267 @default.
- W1531909365 cites W2403035479 @default.
- W1531909365 cites W2570764145 @default.
- W1531909365 cites W2811380766 @default.
- W1531909365 cites W2911546748 @default.
- W1531909365 doi "https://doi.org/10.1137/1.9781611972788.47" @default.
- W1531909365 hasPublicationYear "2008" @default.
- W1531909365 type Work @default.
- W1531909365 sameAs 1531909365 @default.
- W1531909365 citedByCount "22" @default.
- W1531909365 countsByYear W15319093652012 @default.
- W1531909365 countsByYear W15319093652014 @default.
- W1531909365 countsByYear W15319093652016 @default.
- W1531909365 countsByYear W15319093652017 @default.
- W1531909365 countsByYear W15319093652019 @default.
- W1531909365 countsByYear W15319093652020 @default.
- W1531909365 countsByYear W15319093652021 @default.
- W1531909365 crossrefType "proceedings-article" @default.
- W1531909365 hasAuthorship W1531909365A5071708239 @default.
- W1531909365 hasAuthorship W1531909365A5072744508 @default.
- W1531909365 hasConcept C119857082 @default.
- W1531909365 hasConcept C134306372 @default.
- W1531909365 hasConcept C154945302 @default.
- W1531909365 hasConcept C177148314 @default.
- W1531909365 hasConcept C33923547 @default.
- W1531909365 hasConcept C41008148 @default.
- W1531909365 hasConcept C77967617 @default.
- W1531909365 hasConcept C81917197 @default.
- W1531909365 hasConceptScore W1531909365C119857082 @default.
- W1531909365 hasConceptScore W1531909365C134306372 @default.
- W1531909365 hasConceptScore W1531909365C154945302 @default.
- W1531909365 hasConceptScore W1531909365C177148314 @default.
- W1531909365 hasConceptScore W1531909365C33923547 @default.
- W1531909365 hasConceptScore W1531909365C41008148 @default.
- W1531909365 hasConceptScore W1531909365C77967617 @default.
- W1531909365 hasConceptScore W1531909365C81917197 @default.
- W1531909365 hasLocation W15319093651 @default.
- W1531909365 hasOpenAccess W1531909365 @default.
- W1531909365 hasPrimaryLocation W15319093651 @default.
- W1531909365 hasRelatedWork W2597787948 @default.
- W1531909365 hasRelatedWork W2954428433 @default.
- W1531909365 hasRelatedWork W3025582806 @default.
- W1531909365 hasRelatedWork W3047894882 @default.
- W1531909365 hasRelatedWork W3136151706 @default.
- W1531909365 hasRelatedWork W3177723589 @default.
- W1531909365 hasRelatedWork W3196155444 @default.
- W1531909365 hasRelatedWork W3208584567 @default.
- W1531909365 hasRelatedWork W4320063314 @default.
- W1531909365 hasRelatedWork W4366320140 @default.
- W1531909365 isParatext "false" @default.
- W1531909365 isRetracted "false" @default.
- W1531909365 magId "1531909365" @default.
- W1531909365 workType "article" @default.