Publications

See also my Google Scholar

<Preprints>

· Stephen Pasteris, Alberto Rumi, Maximilian Thiessen, Shota Saito, Atsushi Miyauchi, Fabio Vitale and Mark Herbster.  Bandits with Abstention Under Expert Advice. 2024 [arXiv]

<Journal Paper>

· Shota Saito and Mark Herbster. Generalizing p-Laplacian: Spectral Hypergraph Theory and a Partitioning Algorithm. Machine Learning, 112 (1), 241-280, 2023 [Link]

· Shota Saito, Yoshito Hirata, Kazutoshi Sasahara, and Hideyuki Suzuki. Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation. PLoS ONE 10(9): e0139085, 2015 [Link] [Link to Data]

· Shota Saito, Ryota Tomioka, and Kenji Yamanishi. Early Detection of Persistent Topics in Social Networks. Social Network Analysis and Mining, 5(19), pp.1-15, 2015 [pdf] [Link]

<Conference Paper with Peer Review>

· Shota Saito and Mark Herbster. Multi-class Graph Clustering via Approximated Effective p-Resistance, In Proceeding of International Conference on Machine Learning, to appear 2023 [arXiv][code][official] (Acceptance rate - 28%)

· Shota Saito. Hypergraph Embedding: Hypergraph Cut, Kernel k-means, and Heat Kernel. In Proceeding of AAAI Conference on Artificial Intelligence 36(7), 8141-8149, 2022 (Acceptance rate - 15%) [arXiv][code][pdf]

· Shota Saito, Danilo P Mandic, and Hideyuki Suzuki. Hypergraph p-Laplacian: A Differential Geometry View. In Proceeding of AAAI Conference on Artificial Intelligence. pp. 3984-3991, 2018(Acceptance rate - 24%) [arXiv][demo code] [pdf]

· Shota Saito, Ryota Tomioka, and Kenji Yamanishi. Early Detection of Persistent Topics in Social Networks. In Proceeding of Advances in Social Networks in Analysis and Mining. pp. 417 - 424, 2014 (Full Paper: Acceptance rate - 18%) [pdf] [slides] Invited to SNAM Journal paper.

<Conference Paper without Peer Review>

· Shota Saito, Yohei Ikawa, Hideyuki Suzuki and Akiko Murakami, "Early Detection of Disasters with Contextual Information on Twitter," IEICE Tech. Rep., vol. 114, no. 81, NLC2014-2, pp. 7-12, June 2014. (in Japanese) Won the best student paper award

· Akiko Murakami, Miki Enoki and Shota Saito, "A Consideration of User Interest Modeling using Re-sharing Activities in SNS," In Proceeding of The 28th Annual Conference of the Japanese Society for Artificial Intelligence, 2014 (in Japanese) [pdf]

· Shota Saito, Ryota Tomioka and Kenji Yamanishi, “Detecting Long-term Trending Topics in Social Networks,” IEICE Tech. Report, vol. 111, no. 480, IBISML2011-98, pp. 77-84. (in Japanese)