Matches in SemOpenAlex for { <https://semopenalex.org/work/W3090469165> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W3090469165 endingPage "857" @default.
- W3090469165 startingPage "848" @default.
- W3090469165 abstract "Multi-task learning approaches have shown significant improvements in different fields by training different related tasks simultaneously. The multi-task model learns common features among different tasks where they share some layers. However, it is observed that the multi-task learning approach can suffer performance degradation with respect to single task learning in some of the natural language processing tasks, specifically in sequence labelling problems. To tackle this limitation we formulate a simple but effective approach that combines multi-task learning with transfer learning. We use a simple model that comprises of bidirectional long-short term memory and conditional random field. With this simple model, we are able to achieve better F1-score compared to our single task and the multi-task models as well as state-of-the-art multi-task models." @default.
- W3090469165 created "2020-10-08" @default.
- W3090469165 creator A5004305859 @default.
- W3090469165 creator A5068039203 @default.
- W3090469165 creator A5073069826 @default.
- W3090469165 creator A5073627176 @default.
- W3090469165 date "2020-01-01" @default.
- W3090469165 modified "2023-10-14" @default.
- W3090469165 title "Combining Multi-task Learning with Transfer Learning for Biomedical Named Entity Recognition" @default.
- W3090469165 cites W1985871111 @default.
- W3090469165 cites W2378988337 @default.
- W3090469165 cites W2397012302 @default.
- W3090469165 cites W2473930607 @default.
- W3090469165 cites W2510317721 @default.
- W3090469165 cites W2613831280 @default.
- W3090469165 cites W2743028754 @default.
- W3090469165 cites W2806162054 @default.
- W3090469165 cites W2913340405 @default.
- W3090469165 cites W2919115771 @default.
- W3090469165 cites W2937450972 @default.
- W3090469165 cites W2949176808 @default.
- W3090469165 cites W2956147019 @default.
- W3090469165 cites W2962897020 @default.
- W3090469165 cites W2963339489 @default.
- W3090469165 cites W2963453233 @default.
- W3090469165 cites W2987967524 @default.
- W3090469165 cites W2988766056 @default.
- W3090469165 cites W2990167254 @default.
- W3090469165 doi "https://doi.org/10.1016/j.procs.2020.09.080" @default.
- W3090469165 hasPublicationYear "2020" @default.
- W3090469165 type Work @default.
- W3090469165 sameAs 3090469165 @default.
- W3090469165 citedByCount "12" @default.
- W3090469165 countsByYear W30904691652020 @default.
- W3090469165 countsByYear W30904691652021 @default.
- W3090469165 countsByYear W30904691652022 @default.
- W3090469165 countsByYear W30904691652023 @default.
- W3090469165 crossrefType "journal-article" @default.
- W3090469165 hasAuthorship W3090469165A5004305859 @default.
- W3090469165 hasAuthorship W3090469165A5068039203 @default.
- W3090469165 hasAuthorship W3090469165A5073069826 @default.
- W3090469165 hasAuthorship W3090469165A5073627176 @default.
- W3090469165 hasBestOaLocation W30904691651 @default.
- W3090469165 hasConcept C111472728 @default.
- W3090469165 hasConcept C119857082 @default.
- W3090469165 hasConcept C138885662 @default.
- W3090469165 hasConcept C150899416 @default.
- W3090469165 hasConcept C152565575 @default.
- W3090469165 hasConcept C154945302 @default.
- W3090469165 hasConcept C162324750 @default.
- W3090469165 hasConcept C187736073 @default.
- W3090469165 hasConcept C202444582 @default.
- W3090469165 hasConcept C204321447 @default.
- W3090469165 hasConcept C2779135771 @default.
- W3090469165 hasConcept C2780451532 @default.
- W3090469165 hasConcept C2780586882 @default.
- W3090469165 hasConcept C28006648 @default.
- W3090469165 hasConcept C33923547 @default.
- W3090469165 hasConcept C35639132 @default.
- W3090469165 hasConcept C41008148 @default.
- W3090469165 hasConcept C9652623 @default.
- W3090469165 hasConceptScore W3090469165C111472728 @default.
- W3090469165 hasConceptScore W3090469165C119857082 @default.
- W3090469165 hasConceptScore W3090469165C138885662 @default.
- W3090469165 hasConceptScore W3090469165C150899416 @default.
- W3090469165 hasConceptScore W3090469165C152565575 @default.
- W3090469165 hasConceptScore W3090469165C154945302 @default.
- W3090469165 hasConceptScore W3090469165C162324750 @default.
- W3090469165 hasConceptScore W3090469165C187736073 @default.
- W3090469165 hasConceptScore W3090469165C202444582 @default.
- W3090469165 hasConceptScore W3090469165C204321447 @default.
- W3090469165 hasConceptScore W3090469165C2779135771 @default.
- W3090469165 hasConceptScore W3090469165C2780451532 @default.
- W3090469165 hasConceptScore W3090469165C2780586882 @default.
- W3090469165 hasConceptScore W3090469165C28006648 @default.
- W3090469165 hasConceptScore W3090469165C33923547 @default.
- W3090469165 hasConceptScore W3090469165C35639132 @default.
- W3090469165 hasConceptScore W3090469165C41008148 @default.
- W3090469165 hasConceptScore W3090469165C9652623 @default.
- W3090469165 hasLocation W30904691651 @default.
- W3090469165 hasOpenAccess W3090469165 @default.
- W3090469165 hasPrimaryLocation W30904691651 @default.
- W3090469165 hasRelatedWork W2078793151 @default.
- W3090469165 hasRelatedWork W2899863948 @default.
- W3090469165 hasRelatedWork W2914453913 @default.
- W3090469165 hasRelatedWork W2947903144 @default.
- W3090469165 hasRelatedWork W2950021574 @default.
- W3090469165 hasRelatedWork W3023910524 @default.
- W3090469165 hasRelatedWork W3090469165 @default.
- W3090469165 hasRelatedWork W3212915674 @default.
- W3090469165 hasRelatedWork W4206505934 @default.
- W3090469165 hasRelatedWork W4288762748 @default.
- W3090469165 hasVolume "176" @default.
- W3090469165 isParatext "false" @default.
- W3090469165 isRetracted "false" @default.
- W3090469165 magId "3090469165" @default.
- W3090469165 workType "article" @default.