Article

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:https://doi.org/10.1109/TKDE.2019.2955945)

Conference Proceedings

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:https://doi.org/10.24963/ijcai.2020/423)

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:https://doi.org/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:https://doi.org/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:https://doi.org/10.1609/aaai.v33i01.33015264)

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:https://doi.org/10.24963/ijcai.2018/385)

Suzuki, Atsushi, Miyaguchi, Kohei and Yamanishi, Kenji (2017) Structure selection for convolutive non-negative matrix factorization using normalized maximum likelihood coding. In: 2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, Barcelona, pp. 1221-1226. ISBN 978-1509054749 ISSN 2374-8486 (doi:https://doi.org/10.1109/ICDM.2016.0163)