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Items where Greenwich Author is "Wang, Jing"

Items where Greenwich Author is "Wang, Jing"

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Number of items: 13.

Machine Learning: Classification Machine Learning: Multi-instance; Multi-label; Multi-view learning Data Mining: Classification, Semi-Supervised Learning

Huang, Jun, Xu, Linchuan, Wang, Jing, Feng, Lei and Yamanishi, Kenji (2020) Discovering latent class labels for multi-label learning. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization (IJCAI), pp. 3058-3064. ISBN 978-0999241165 (doi:https://doi.org/10.24963/ijcai.2020/423)

Multi-view representation learning, Subspace clustering, Low-rank tensor, Constraint matrix

Zhang, Changqing ORCID: 0000-0003-1410-6650, Fu, Huazhu, Wang, Jing, Li, Wen, Cao, Xiaochun and Hu, Qinghua (2020) Tensorized multi-view subspace representation learning. International Journal of Computer Vision, 128 (8-9). pp. 2344-2361. ISSN 0920-5691 (Print), 1573-1405 (Online) (doi:https://doi.org/10.1007/s11263-020-01307-0)

community detection, semi-supervised learning

Yang, Liang, Ge, Meng, Jin, Di, He, Dongxiao, Fu, Huazhu, Wang, Jing and Cao, Xiaochun (2017) Exploring the roles of cannot-link constraint in community detection via multi-variance mixed Gaussian generative model. PLoS One, 12 (7):e0178029. ISSN 1932-6203 (Online) (doi:https://doi.org/10.1371/journal.pone.0178029)

diversity representation, multiview learning, non-negative matrix factorization (NMF)

Wang, Jing, Tian, Feng, Yu, Hongchuan, Liu, Chang Hong, Zhan, Kun and Wang, Xiao (2017) Diverse non-negative matrix factorization for multiview data representation. IEEE Transactions on Cybernetics, 48 (9). pp. 2620-2632. ISSN 2168-2267 (Print), 2168-2275 (Online) (doi:https://doi.org/10.1109/TCYB.2017.2747400)

low rank representation, subspace clustering, semi-supervised learning

Wang, Jing, Wang, Xiao, Tian, Feng, Liu, Chang Hong and Yu, Hongchuan (2016) Constrained low-rank representation for robust subspace clustering. IEEE Transactions on Cybernetics, 47 (12). pp. 4534-4546. ISSN 2168-2267 (Print), 2168-2275 (Online) (doi:https://doi.org/10.1109/TCYB.2016.2618852)

multi-component, NMF, clustering

Wang, Jing, Tian, Feng, Wang, Xiao, Yu, Hongchuan, Liu, Chang Hong and Yang, Liang (2017) Multi-component nonnegative matrix factorization. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence, pp. 2922-2928. ISBN 978-0999241103 (doi:https://doi.org/10.24963/ijcai.2017/407)

network embedding, heterogeneous information networks, multi-label classification, link prediction

Xu, Linchuan, Wang, Jing, He, Lifang, Cao, Jiannong, Wei, Xiaokai, Yu, Phillip S. and Yamanishi, Kenji (2019) MixSp: a framework for embedding heterogeneous information networks with arbitrary number of node and edge types. IEEE Transactions on Knowledge and Data Engineering. ISSN 1041-4347 (Print), 1558-2191 (Online) (In Press) (doi:https://doi.org/10.1109/TKDE.2019.2955945)

network embedding, nonnegative matrix factorization, unsupervised learnng

Wang, Xiao, Cui, Peng, Wang, Jing, Pei, Jian, Zhu, Wenwu and Yang, Shiqiang (2017) Community preserving network embedding. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17). AAAI Press, pp. 203-209.

nonnegative matrix factorization, ordered structure, unsupervised learning

Wang, Jing, Tian, Feng, Liu, Chang Hong, Yu, Hongchuan, Wang, Xiao and Tang, Xianchao (2017) Robust nonnegative matrix factorization with ordered structure constraints. In: 2017 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 478-485. ISBN 978-1509061839 ISSN 2161-4407 (Online) (doi:https://doi.org/10.1109/IJCNN.2017.7965892)

subspace clustering, attribute learning, unsupervised learning

Wang, Jing, Xu, Linchuan, Tian, Feng, Suzuki, Atsushi, Zhang, Changqing and Yamanishi, Kenji (2019) Attributed subspace clustering. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence, pp. 3719-3725. ISBN 978-0999241141 (doi:https://doi.org/10.24963/ijcai.2019/516)

subspace clustering, unsupervised learning, orderly embedding

Wang, Jing, Suzuki, Atsushi, Xu, Linchuan, Tian, Feng, Yang, Liang and Yamanishi, Kenji (2019) Orderly subspace clustering. In: Proceedings of the AAAI Conference on Artificial Intelligence. AAAI Press, Palo Alto, California USA, pp. 5264-5272. ISBN 978-1577358091 ISSN 2159-5399 (Print), 2374-3468 (Online) (doi:https://doi.org/10.1609/aaai.v33i01.33015264)

trust prediction, low-rank representation

Wang, Xiao, Zhang, Ziwei, Wang, Jing, Cui, Peng and Yang, Shiqiang (2018) Power-law distribution aware trust prediction. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence, pp. 3564-3570. ISBN 978-0999241127 (doi:https://doi.org/10.24963/ijcai.2018/495)

unsupervised learning, multiview clustering, image retrieval, graph learning

Zhan, Kun, Nie, Feiping, Wang, Jing and Yang, Yi (2018) Multiview consensus graph clustering. IEEE Transactions on Image Processing, 28 (3). pp. 1261-1270. ISSN 1057-7149 (Print), 1941-0042 (Online) (doi:https://doi.org/10.1109/TIP.2018.2877335)

This list was generated on Thu Feb 25 02:04:51 2021 UTC.