1 code implementation • 30 Nov 2023 • Shintaro Fukushima, Kenji Yamanishi
The parameter specifying the summary graph is then optimized so that the accuracy of change detection is guaranteed to suppress Type I error probability (probability of raising false alarms) to be less than a given confidence level.
1 code implementation • 2 Oct 2023 • Xiaohang Xu, Toyotaro Suzumura, Jiawei Yong, Masatoshi Hanai, Chuang Yang, Hiroki Kanezashi, Renhe Jiang, Shintaro Fukushima
Extracting distinct fine-grained features unique to each piece of information is difficult since temporal information often includes spatial information, as users tend to visit nearby POIs.
1 code implementation • 12 Dec 2022 • Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Toyotaro Suzumura, Shintaro Fukushima
Spatio-temporal modeling as a canonical task of multivariate time series forecasting has been a significant research topic in AI community.
1 code implementation • 27 Nov 2022 • Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Shintaro Fukushima, Toyotaro Suzumura
Traffic forecasting as a canonical task of multivariate time series forecasting has been a significant research topic in AI community.
Ranked #1 on Traffic Prediction on EXPY-TKY
no code implementations • 18 Nov 2020 • Shintaro Fukushima, Kenji Yamanishi
This paper addresses the issue of detecting hierarchical changes in latent variable models (HCDL) from data streams.
1 code implementation • 23 Jul 2020 • Shintaro Fukushima, Atsushi Nitanda, Kenji Yamanishi
We address the relation between the two parameters: one is the step size of the stochastic approximation, and the other is the threshold parameter of the norm of the stochastic update.