Learning Continually from Low-shot Data Stream
Learning Continually from Low-shot Data Stream
About this item
Full title
Author / Creator
Le, Canyu , Xihan Wei , Wang, Biao , Zhang, Lei and Chen, Zhonggui
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
Formats
Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
Subjects
More information
Scope and Contents
Contents
While deep learning has achieved remarkable results on various applications, it is usually data hungry and struggles to learn over non-stationary data stream. To solve these two limits, the deep learning model should not only be able to learn from a few of data, but also incrementally learn new concepts from data stream over time without forgetting...
Alternative Titles
Full title
Learning Continually from Low-shot Data Stream
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2281561679
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2281561679
Other Identifiers
E-ISSN
2331-8422
