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2010 – 2019
- 2019
[c8]Katsuya Ito, Akira Kinoshita, Masashi Yoshikawa:
Structural Change Point Detection Using A Large Random Matrix and Sparse Modeling. EDBT/ICDT Workshops 2019- 2018
- [c7]Takaya Kawakatsu
, Akira Kinoshita, Kenro Aihara, Atsuhiro Takasu, Jun Adachi:
Adversarial Spiral Learning Approach to Strain Analysis for Bridge Damage Detection. DaWaK 2018: 49-58 - 2016
- [j2]Takaya Kawakatsu, Akira Kinoshita, Atsuhiro Takasu, Jun Adachi:
Divide-and-Conquer Parallelism for Learning Mixture Models. Trans. Large Scale Data Knowl. Centered Syst. 28: 23-47 (2016) - [c6]Akira Kinoshita, Atsuhiro Takasu, Kenro Aihara, Jun Ishii, Hisashi Kurasawa, Hiroshi Sato, Motonori Nakamura, Jun Adachi:
GPS Trajectory Data Enrichment based on a Latent Statistical Model. ICPRAM 2016: 255-262 - [c5]Akira Kinoshita, Atsuhiro Takasu, Jun Adachi:
Latent Variable Model for Weather-Aware Traffic State Analysis. ISIP 2016: 51-65 - [c4]Bin Piao, Kenro Aihara, Akira Kinoshita, Atsuhiro Takasu, Jun Adachi:
Estimating Road Surface Condition Using Crowdsourcing. ISIP 2016: 66-81 - 2015
- [j1]Akira Kinoshita, Atsuhiro Takasu, Jun Adachi:
Real-time traffic incident detection using a probabilistic topic model. Inf. Syst. 54: 169-188 (2015) - [c3]Takaya Kawakatsu, Akira Kinoshita, Atsuhiro Takasu, Jun Adachi:
Highly Efficient Parallel Framework: A Divide-and-Conquer Approach. DEXA (2) 2015: 162-176 - 2014
- [c2]Akira Kinoshita, Atsuhiro Takasu, Jun Adachi:
Real-time traffic incident detection using probe-car data on the Tokyo Metropolitan Expressway. IEEE BigData 2014 - [c1]Akira Kinoshita, Atsuhiro Takasu, Jun Adachi:
Traffic Incident Detection Using Probabilistic Topic Model. EDBT/ICDT Workshops 2014: 323-330
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