Matches in SemOpenAlex for { <https://semopenalex.org/work/W4289744518> ?p ?o ?g. }
Showing items 1 to 65 of
65
with 100 items per page.
- W4289744518 abstract "Although deep learning approaches have stood out in recent years due to their state-of-the-art results, they continue to suffer from catastrophic forgetting, a dramatic decrease in overall performance when training with new classes added incrementally. This is due to current neural network architectures requiring the entire dataset, consisting of all the samples from the old as well as the new classes, to update the model -a requirement that becomes easily unsustainable as the number of classes grows. We address this issue with our approach to learn deep neural networks incrementally, using new data and only a small exemplar set corresponding to samples from the old classes. This is based on a loss composed of a distillation measure to retain the knowledge acquired from the old classes, and a cross-entropy loss to learn the new classes. Our incremental training is achieved while keeping the entire framework end-to-end, i.e., learning the data representation and the classifier jointly, unlike recent methods with no such guarantees. We evaluate our method extensively on the CIFAR-100 and ImageNet (ILSVRC 2012) image classification datasets, and show state-of-the-art performance." @default.
- W4289744518 created "2022-08-04" @default.
- W4289744518 creator A5041004091 @default.
- W4289744518 creator A5042354417 @default.
- W4289744518 creator A5045217258 @default.
- W4289744518 creator A5049440980 @default.
- W4289744518 creator A5077255817 @default.
- W4289744518 date "2018-07-25" @default.
- W4289744518 modified "2023-10-16" @default.
- W4289744518 title "End-to-End Incremental Learning" @default.
- W4289744518 doi "https://doi.org/10.48550/arxiv.1807.09536" @default.
- W4289744518 hasPublicationYear "2018" @default.
- W4289744518 type Work @default.
- W4289744518 citedByCount "0" @default.
- W4289744518 crossrefType "posted-content" @default.
- W4289744518 hasAuthorship W4289744518A5041004091 @default.
- W4289744518 hasAuthorship W4289744518A5042354417 @default.
- W4289744518 hasAuthorship W4289744518A5045217258 @default.
- W4289744518 hasAuthorship W4289744518A5049440980 @default.
- W4289744518 hasAuthorship W4289744518A5077255817 @default.
- W4289744518 hasBestOaLocation W42897445181 @default.
- W4289744518 hasConcept C108583219 @default.
- W4289744518 hasConcept C119857082 @default.
- W4289744518 hasConcept C138885662 @default.
- W4289744518 hasConcept C153180895 @default.
- W4289744518 hasConcept C154945302 @default.
- W4289744518 hasConcept C167981619 @default.
- W4289744518 hasConcept C2984842247 @default.
- W4289744518 hasConcept C41008148 @default.
- W4289744518 hasConcept C41895202 @default.
- W4289744518 hasConcept C50644808 @default.
- W4289744518 hasConcept C51632099 @default.
- W4289744518 hasConcept C7149132 @default.
- W4289744518 hasConcept C74296488 @default.
- W4289744518 hasConcept C95623464 @default.
- W4289744518 hasConceptScore W4289744518C108583219 @default.
- W4289744518 hasConceptScore W4289744518C119857082 @default.
- W4289744518 hasConceptScore W4289744518C138885662 @default.
- W4289744518 hasConceptScore W4289744518C153180895 @default.
- W4289744518 hasConceptScore W4289744518C154945302 @default.
- W4289744518 hasConceptScore W4289744518C167981619 @default.
- W4289744518 hasConceptScore W4289744518C2984842247 @default.
- W4289744518 hasConceptScore W4289744518C41008148 @default.
- W4289744518 hasConceptScore W4289744518C41895202 @default.
- W4289744518 hasConceptScore W4289744518C50644808 @default.
- W4289744518 hasConceptScore W4289744518C51632099 @default.
- W4289744518 hasConceptScore W4289744518C7149132 @default.
- W4289744518 hasConceptScore W4289744518C74296488 @default.
- W4289744518 hasConceptScore W4289744518C95623464 @default.
- W4289744518 hasLocation W42897445181 @default.
- W4289744518 hasOpenAccess W4289744518 @default.
- W4289744518 hasPrimaryLocation W42897445181 @default.
- W4289744518 hasRelatedWork W2791691546 @default.
- W4289744518 hasRelatedWork W2950066684 @default.
- W4289744518 hasRelatedWork W2953348396 @default.
- W4289744518 hasRelatedWork W3082895349 @default.
- W4289744518 hasRelatedWork W3158264953 @default.
- W4289744518 hasRelatedWork W4288853838 @default.
- W4289744518 hasRelatedWork W4289744518 @default.
- W4289744518 hasRelatedWork W4298388782 @default.
- W4289744518 hasRelatedWork W4310989423 @default.
- W4289744518 hasRelatedWork W4312831135 @default.
- W4289744518 isParatext "false" @default.
- W4289744518 isRetracted "false" @default.
- W4289744518 workType "article" @default.