Publications

Ryuichi Sudo, and Hiroyuki Toda, "Understanding Human Mobility Using Trajectories and Corresponding GIS Data", In Proceedings of the 35th International Conference on Database and Expert Systems Applications (DEXA2024), pp.000-000, Naples, Italy, August 2024. (to appear) 

Tomoki Kawabata, and Hiroyuki Toda, "Spatio-Temporal Graph Modeling with Knowledge Transfer for Traffic Prediction at Evolving Traffic Measurement Points", In Proceedings of the 35th International Conference on Database and Expert Systems Applications (DEXA2024), pp.000-000, Naples, Italy, August 2024. (to appear) 

Yuya Hikima, Yasunori Akagi, Masahiro Kohjima, Takeshi Kurashima, and Hiroyuki Toda, "Price and Time Proposal Optimization for Ride-Hailing Services Based on Individual Utilities", Transactions of the Japanese Society for Artificial Intelligence, Vol. 38, Issue 1, Page C-M13_1-12, January 2023. J-STAGE

Masahiro Kohjima, Takeshi Kurashima, and Hiroyuki Toda, "Inverse Problem of Censored Markov Chain: Estimating Markov Chain Parameters from Censored Transition Data", Proc. the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2023), May 2023.

Takeshi Kurashima, Tomoharu Iwata, Tomu Tominaga, Shuhei Yamamoto, Hiroyuki Toda, and Kazuhisa Takemura, "Personal History Affects Reference Points: A Case Study of Codeforces", Proc. the 17th International Conference on Web and Social Media (ICWSM 2023), June 2023. Conference Site

Hiroki Kanagawa, Yusuke Ijima, and Hiroyuki Toda, "Joint Modeling of Multi-Sample and Subband Signals for Fast Neural Vocoding on CPU", Proc. 23rd INTERSPEECH Conference (INTERSPEECH 2022), pp. 1626-1630, Sep. 2022.

Hideaki Kim, Taichi Asami, and Hiroyuki Toda, "Fast Bayesian Inference of Point Process Intensity as Function of Covariates", Proc. the 36th Conference on Neural Information Processing Systems (NeurIPS 2022), Dec. 2022.

Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, and Hiroyuki Toda, "MAP inference algorithms without approximation for collective graphical models on path graphs via discrete difference of convex algorithm", Machine Learning, December 2022. Springer