When Semantically Consistent Encoding Meets View-Label Heterogeneity Modeling: A Unified Framework for Incomplete Multi-View Multi-Label Learning
- DOI
- 10.1109/tpami.2026.3728832
- Published
- 2026
- Container
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tpami.2026.3728832,
title = {When Semantically Consistent Encoding Meets View-Label Heterogeneity Modeling: A Unified Framework for Incomplete Multi-View Multi-Label Learning},
author = {Chengliang Liu and Bo Li and Bob Zhang and Yanghao Zhou and Jie Wen and Wenwu Wang},
year = {2026},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
doi = {10.1109/tpami.2026.3728832},
url = {https://doi.org/10.1109/tpami.2026.3728832}
}RIS
TY - JOUR TI - When Semantically Consistent Encoding Meets View-Label Heterogeneity Modeling: A Unified Framework for Incomplete Multi-View Multi-Label Learning AU - Chengliang Liu AU - Bo Li AU - Bob Zhang AU - Yanghao Zhou AU - Jie Wen AU - Wenwu Wang PY - 2026 JO - IEEE Transactions on Pattern Analysis and Machine Intelligence DO - 10.1109/tpami.2026.3728832 UR - https://doi.org/10.1109/tpami.2026.3728832 ER -
APA
Liu, C., Li, B., Zhang, B., Zhou, Y., Wen, J., & Wang, W. (2026). When Semantically Consistent Encoding Meets View-Label Heterogeneity Modeling: A Unified Framework for Incomplete Multi-View Multi-Label Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2026.3728832
Source records
- crossref · retrieved 2026-09-24T23:49:21.809Z