Suzuki, Atsushi, Nitanda, Atsushi, Suzuki, Taiji, Wang, Jing, Tian, Feng and Yamanishi, Kenji (2023) Tight and fast generalization error bound of graph embedding in metric space. In: Proceedings of the 40th International Conference on Machine Learning. Volume 202: International Conference on Machine Learning, 23rd - 29th July 2023, Honolulu, Hawaii, USA. Proceedings of Machine Learning Research (PMLR) Press - Journal of Machine Learning Research (JMLR), Cambridge MA, USA, pp. 33268-33284. ISSN 1938-7228 (Print), 2640-3498 (Online)

Suzuki, Atsushi, Nitanda, Atsushi, Wang, Jing, Xu, Linchuan, Yamanishi, Kenji and Cavazza, Marc (2021) Generalization Error Bound for Hyperbolic Ordinal Embedding. In: Proceedings of the 38th International Conference on Machine Learning. Volume 139: International Conference on Machine Learning, 18th - 24th July 2021, Virtual. Proceedings of Machine Learning Research (PMLR) Press - Journal of Machine Learning Research (JMLR), Cambridge MA, USA, pp. 10011-10021. ISSN 1938-7228 (Print), 2640-3498 (Online)

Suzuki, Atsushi, Suzuki, Nitanda, Wang, Jing, Xu, Linchuan, Yamanishi, Kenji and Cavazza, Marc (2021) Generalization error bounds for graph embedding using negative sampling: linear vs hyperbolic. In: Advances in Neural Information Processing Systems (NeurIPS 2021). Curran Associates Inc. - Neural Information Processing Systems Foundation Inc. (NeurIPS) - ACM, New York, US, 1243 -1255. ISBN 978-1713845393

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:10.24963/ijcai.2020/423)

Zhang, Changqing ORCID: https://orcid.org/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:10.1007/s11263-020-01307-0)

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, 33 (6). pp. 2627-2639. ISSN 1041-4347 (Print), 1558-2191 (Online) (doi:10.1109/TKDE.2019.2955945)

Suzuki, Atsushi, Wang, Jing, Tian, Feng, Nitanda, Atsushi and Yamanishi, Kenji (2019) Hyperbolic ordinal embedding. In: Asian Conference on Machine Learning, 17-19 November 2019, Nagoya, Japan. Proceedings of Machine Learning Research, 101 . MIR, Moscow, Russia, pp. 1065-1080.

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:10.24963/ijcai.2019/516)

Zheng, Yuhui, Xu, Linchuan, Kiwaki, Taichi, Wang, Jing, Murata, Hiroshi, Asaoka, Ryo and Yamanishi, Kenji (2019) Glaucoma progression prediction using retinal thickness via latent space linear regression. In: KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Association for Computing Machinery, pp. 2278-2286. ISBN 978-1450362016 (doi:10.1145/3292500.3330757)

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:10.1609/aaai.v33i01.33015264)

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:10.1109/TIP.2018.2877335)

Wang, Jing, Tian, Feng, Liu, Weiwei, Wang, Xiao, Zhang, Wenjie and Yamanishi, Kenji (2018) Ranking preserving nonnegative matrix factorization. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence, pp. 2776-2782. ISBN 978-0999241127 (doi:10.24963/ijcai.2018/385)

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:10.24963/ijcai.2018/495)

Zhan, Kun, Shi, Jinhui, Wang, Jing, Wang, Haibo and Xie, Yuange (2018) Adaptive structure concept factorization for multiview clustering. Neural Computation, 30 (4). pp. 1080-1103. ISSN 0899-7667 (Print), 1530-888X (Online) (doi:10.1162/NECO_a_01055)

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:10.1109/TCYB.2017.2747400)

Shantz, Amanda, Wang, Jing and Malik, Amina (2017) Disability status, individual variable pay, and pay satisfaction: does relational and institutional trust make a difference? Human Resource Management, 57 (1). pp. 365-380. ISSN 0090-4848 (Print), 1099-050X (Online) (doi:10.1002/hrm.21845)

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:10.24963/ijcai.2017/407)

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:10.1371/journal.pone.0178029)

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:10.1109/IJCNN.2017.7965892)

Zhan, Kun, Shi, Jinhui, Wang, Jing and Tian, Feng (2017) Graph-regularized concept factorization for multi-view document clustering. Journal of Visual Communication and Image Representation, 48. pp. 411-418. ISSN 1047-3203 (doi:10.1016/j.jvcir.2017.02.019)

Tang, Xianchao, Xu, Tao, Feng, Xia, Yang, Guoqing, Wang, Jing, Li, Qiannan, Liu, Yanbei and Wang, Xiao (2017) Learning community structures: global and local perspectives. Neurocomputing, 239. pp. 249-256. ISSN 0925-2312 (doi:10.1016/j.neucom.2017.02.026)

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.

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:10.1109/TCYB.2016.2618852)

Wang, Jing, Wang, Xiao, Tian, Feng, Liu, Chang Hong, Yu, Hongchuan and Liu, Yanbei (2016) Adaptive multi-view semi-supervised nonnegative matrix factorization. In: ICONIP 2016: Neural Information Processing. Lecture Notes in Computer Science, 9948 . Springer, pp. 435-444. ISBN 978-3319466712 ISSN 0302-9743 (Print), 1611-3349 (Online) (doi:10.1007/978-3-319-46672-9_49)

Liu, Yanbei, Liu, Kaihua, Zhang, Changqing, Wang, Jing and Wang, Xiao (2016) Unsupervised feature selection via diversity-induced self-representation. Neurocomputing, 219. pp. 350-363. ISSN 0925-2312 (doi:10.1016/j.neucom.2016.09.043)

Wang, Jing, Tian, Feng, Liu, Chang Hong and Wang, Xiao (2015) Robust semi-supervised nonnegative matrix factorization. In: 2015 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1-8. ISBN 978-1479919604 ISSN 2161-4393 (Print), 2161-4407 (Online) (doi:10.1109/IJCNN.2015.7280422)

Shantz, Amanda, Wang, Jing and Malik, Amina (2015) "The Relationships Among Merit Pay, Disability Status, and Trust in Management on Job Satisfaction". In: Academy of Management Conference. (doi:10.5465/AMBPP.2015.10249abstract)