Matches in SemOpenAlex for { <https://semopenalex.org/work/W2115431796> ?p ?o ?g. }
Showing items 1 to 68 of
68
with 100 items per page.
- W2115431796 abstract "Train a neural network with large dataset need a long training time. This paper presents a technique to reduce training time by divide a large dataset into n subsets and use those subsets to train multiple neural networks. In final, knowledge of trained networks are combined into a one network. The results from an experiment show that our technique has the same error like a network that trained by whole dataset but need less training time." @default.
- W2115431796 created "2016-06-24" @default.
- W2115431796 creator A5076276278 @default.
- W2115431796 creator A5080104473 @default.
- W2115431796 date "2014-05-01" @default.
- W2115431796 modified "2023-09-25" @default.
- W2115431796 title "Combining nodes in multiple neural network on large datasets" @default.
- W2115431796 cites W2029409343 @default.
- W2115431796 cites W2096267903 @default.
- W2115431796 cites W2146440428 @default.
- W2115431796 cites W2162848357 @default.
- W2115431796 cites W2533711760 @default.
- W2115431796 cites W2535072857 @default.
- W2115431796 doi "https://doi.org/10.1109/dictap.2014.6821651" @default.
- W2115431796 hasPublicationYear "2014" @default.
- W2115431796 type Work @default.
- W2115431796 sameAs 2115431796 @default.
- W2115431796 citedByCount "0" @default.
- W2115431796 crossrefType "proceedings-article" @default.
- W2115431796 hasAuthorship W2115431796A5076276278 @default.
- W2115431796 hasAuthorship W2115431796A5080104473 @default.
- W2115431796 hasConcept C119857082 @default.
- W2115431796 hasConcept C121332964 @default.
- W2115431796 hasConcept C124101348 @default.
- W2115431796 hasConcept C153294291 @default.
- W2115431796 hasConcept C154945302 @default.
- W2115431796 hasConcept C175202392 @default.
- W2115431796 hasConcept C2777211547 @default.
- W2115431796 hasConcept C41008148 @default.
- W2115431796 hasConcept C50644808 @default.
- W2115431796 hasConcept C51632099 @default.
- W2115431796 hasConceptScore W2115431796C119857082 @default.
- W2115431796 hasConceptScore W2115431796C121332964 @default.
- W2115431796 hasConceptScore W2115431796C124101348 @default.
- W2115431796 hasConceptScore W2115431796C153294291 @default.
- W2115431796 hasConceptScore W2115431796C154945302 @default.
- W2115431796 hasConceptScore W2115431796C175202392 @default.
- W2115431796 hasConceptScore W2115431796C2777211547 @default.
- W2115431796 hasConceptScore W2115431796C41008148 @default.
- W2115431796 hasConceptScore W2115431796C50644808 @default.
- W2115431796 hasConceptScore W2115431796C51632099 @default.
- W2115431796 hasLocation W21154317961 @default.
- W2115431796 hasOpenAccess W2115431796 @default.
- W2115431796 hasPrimaryLocation W21154317961 @default.
- W2115431796 hasRelatedWork W1499489070 @default.
- W2115431796 hasRelatedWork W1544416978 @default.
- W2115431796 hasRelatedWork W1586547218 @default.
- W2115431796 hasRelatedWork W1994157250 @default.
- W2115431796 hasRelatedWork W2015745559 @default.
- W2115431796 hasRelatedWork W2023798383 @default.
- W2115431796 hasRelatedWork W2096531490 @default.
- W2115431796 hasRelatedWork W2097529207 @default.
- W2115431796 hasRelatedWork W2121340621 @default.
- W2115431796 hasRelatedWork W2138742345 @default.
- W2115431796 hasRelatedWork W2168808613 @default.
- W2115431796 hasRelatedWork W2220284787 @default.
- W2115431796 hasRelatedWork W2588772706 @default.
- W2115431796 hasRelatedWork W3144065544 @default.
- W2115431796 hasRelatedWork W3200885138 @default.
- W2115431796 hasRelatedWork W1558493948 @default.
- W2115431796 hasRelatedWork W2273926668 @default.
- W2115431796 hasRelatedWork W3096212889 @default.
- W2115431796 hasRelatedWork W3155872544 @default.
- W2115431796 hasRelatedWork W3181166861 @default.
- W2115431796 isParatext "false" @default.
- W2115431796 isRetracted "false" @default.
- W2115431796 magId "2115431796" @default.
- W2115431796 workType "article" @default.