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Akihito Sudo
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2020 – today
- 2021
- [j6]Keita Tokuda, Naoya Fujiwara, Akihito Sudo, Yuichi Katori:
Chaos may enhance expressivity in cerebellar granular layer. Neural Networks 136: 72-86 (2021) - [j5]Takafumi Sakamoto, Akihito Sudo, Yugo Takeuchi:
Investigation of Model for Initial Phase of Communication: Analysis of Humans Interaction by Robot. ACM Trans. Hum. Robot Interact. 10(2): 14:1-14:27 (2021) - [i2]Akihito Sudo:
Fundamental Advantage of Feedback Control Based on a Generalized Second Law of Thermodynamics. CoRR abs/2108.00738 (2021) - [i1]Akihito Sudo, Teck-Hou Teng, Masaki Yamaguchi, Yoshinori Tone:
LassoLayer: Nonlinear Feature Selection by Switching One-to-one Links. CoRR abs/2108.12165 (2021) - 2020
- [c8]Keita Tokuda, David Kaschub, Takuma Ota, Yasunobu Hashimoto, Naoya Fujiwara, Akihito Sudo:
Prediction of Student Performance in Abacus-Based Calculation Using Matrix Factorization. UMAP (Adjunct Publication) 2020: 114-118
2010 – 2019
- 2019
- [e1]Akihito Sudo, Yoshihide Sekimoto, Lau Hoong Chin, Xuan Song, Takahiro Yabe:
Proceedings of the 2nd ACM SIGSPATIAL Workshop on Prediction of Human Mobility, PredictGIS 2018, Seattle, WA, USA, November 6, 2018. ACM 2019, ISBN 978-1-4503-6042-5 [contents] - 2018
- [j4]Akihito Sudo, Yoshihide Sekimoto, Lau Honng Chuin, Xuan Song, Takahiro Yabe:
Predictgis 2018 workshop report held in conjunction with ACM SIGSPATIAL 2018. ACM SIGSPATIAL Special 10(3): 26-27 (2018) - 2017
- [j3]Akihito Sudo, Takahiro Yabe, Yoshihide Sekimoto:
PredictGIS 2017 workshop report held in conjunction with ACM SIGSPATIAL 2017. ACM SIGSPATIAL Special 9(3): 30-31 (2017) - [c7]Akihito Sudo, Teck-Hou Teng, Hoong Chuin Lau, Yoshihide Sekimoto:
Predicting Indoor Crowd Density using Column-Structured Deep Neural Network. PredictGIS@SIGSPATIAL 2017: 7:1-7:7 - 2016
- [c6]Akihito Sudo, Takehiro Kashiyama, Takahiro Yabe, Hiroshi Kanasugi, Xuan Song, Tomoyuki Higuchi, Shin'ya Nakano, Masaya M. Saito, Yoshihide Sekimoto:
Particle filter for real-time human mobility prediction following unprecedented disaster. SIGSPATIAL/GIS 2016: 5:1-5:10 - [c5]Takahiro Yabe, Kota Tsubouchi, Akihito Sudo, Yoshihide Sekimoto:
A framework for evacuation hotspot detection after large scale disasters using location data from smartphones: case study of Kumamoto earthquake. SIGSPATIAL/GIS 2016: 44:1-44:10 - [c4]Takahiro Yabe, Kota Tsubouchi, Akihito Sudo, Yoshihide Sekimoto:
Predicting irregular individual movement following frequent mid-level disasters using location data from smartphones. SIGSPATIAL/GIS 2016: 54:1-54:4 - [c3]Yoshihide Sekimoto, Akihito Sudo, Takehiro Kashiyama, Toshikazu Seto, Hideki Hayashi, Akinori Asahara, Hiroki Ishizuka, Satoshi Nishiyama:
Real-time people movement estimation in large disasters from several kinds of mobile phone data. UbiComp Adjunct 2016: 1426-1434 - 2010
- [j2]Furao Shen, Akihito Sudo, Osamu Hasegawa:
An online incremental learning pattern-based reasoning system. Neural Networks 23(1): 135-143 (2010)
2000 – 2009
- 2009
- [j1]Akihito Sudo, Akihiro Sato, Osamu Hasegawa:
Associative Memory for Online Learning in Noisy Environments Using Self-Organizing Incremental Neural Network. IEEE Trans. Neural Networks 20(6): 964-972 (2009) - 2007
- [c2]Akihito Sudo, Manabu Tsuboyama, Chenli Zhang, Akihiro Sato, Osamu Hasegawa:
Pattern-Based Reasoning System Using Self-incremental Neural Network for Propositional Logic. ICONIP (1) 2007: 338-347 - [c1]Akihito Sudo, Akihiro Sato, Osamu Hasegawa:
Associative Memory for Online Incremental Learning in Noisy Environments. IJCNN 2007: 619-624
Coauthor Index
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