| dc.contributor.author | Peng, P | en_US |
| dc.contributor.author | Tian, Y | en_US |
| dc.contributor.author | Xiang, T | en_US |
| dc.contributor.author | Wang, Y | en_US |
| dc.contributor.author | Pontil, M | en_US |
| dc.contributor.author | Huang, T | en_US |
| dc.date.accessioned | 2017-07-06T14:15:11Z | |
| dc.date.available | 2017-06-29 | en_US |
| dc.date.issued | 2018-07 | en_US |
| dc.date.submitted | 2017-06-30T09:36:42.480Z | |
| dc.identifier.issn | 0162-8828 | en_US |
| dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/24746 | |
| dc.description.sponsorship | This work is partially supported by grants from the
National Natural Science Foundation of China under
contract No. 61390515, No. U1611461, and No.
61425025, and the National Basic Research Program
of China under Grant No. 2015CB351806. | en_US |
| dc.format.extent | 1625 - 1638 | en_US |
| dc.relation.ispartof | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | en_US |
| dc.rights | This is a pre-copyedited, author-produced version of an article accepted for publication in IEEE Transactions on Pattern Analysis and Machine Intelligence following peer review. | |
| dc.subject | Attribute learning | en_US |
| dc.subject | dictionary learning | en_US |
| dc.subject | multi-task learning | en_US |
| dc.subject | zero-shot learning | en_US |
| dc.subject | person re-identification | en_US |
| dc.subject | transfer learning | en_US |
| dc.title | Joint Semantic and Latent Attribute Modelling for Cross-Class Transfer Learning | en_US |
| dc.type | Article | |
| dc.rights.holder | © IEEE 2017 | |
| dc.identifier.doi | 10.1109/TPAMI.2017.2723882 | en_US |
| pubs.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000434294800007&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
| pubs.issue | 7 | en_US |
| pubs.notes | Not known | en_US |
| pubs.publication-status | Published | en_US |
| pubs.volume | 40 | en_US |
