How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?

Zhong, L; Fang, Z; Liu, F; Lu, J; Yuan, B; Zhang, G

How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?

Zhong, L Fang, Z Liu, F

Lu, J Yuan, B Zhang, G

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Publisher:: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE
Publication Type:: Conference Proceeding
Citation:: THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35, pp. 11079-11087
Issue Date:: 2021-01-01

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Field	Value	Language
dc.contributor.author	Zhong, L
dc.contributor.author	Fang, Z
dc.contributor.author	Liu, F https://orcid.org/0000-0002-5005-9129
dc.contributor.author	Lu, J
dc.contributor.author	Yuan, B
dc.contributor.author	Zhang, G
dc.date	2021-02-02
dc.date.accessioned	2022-07-05T01:50:14Z
dc.date.available	2022-07-05T01:50:14Z
dc.date.issued	2021-01-01
dc.identifier.citation	THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35, pp. 11079-11087
dc.identifier.issn	2159-5399
dc.identifier.issn	2374-3468
dc.identifier.uri	http://hdl.handle.net/10453/158645
dc.language	en
dc.publisher	ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE
dc.relation.ispartof	THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE
dc.relation.ispartof	35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence
dc.relation.ispartofseries	AAAI Conference on Artificial Intelligence
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
dc.type	Conference Proceeding
utslib.citation.volume	35
utslib.location.activity	ELECTR NETWORK
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-05T01:50:13Z
pubs.finish-date	2021-02-09
pubs.publication-status	Published
pubs.start-date	2021-02-02
pubs.volume	35

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http://hdl.handle.net/10453/158645