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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 5 of 5  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
ET 2024-01-20
13:35		 Kyoto Kyoto University Yoshida Campus / Online
(Primary: On-site, Secondary: Online)		 Evaluation of the Impact on Mentors in a Mentalization Support System for Generating Questions to Mentee
Kaisei Ominami, Shota Tatarai, Kohei Okuoka (Nihon Univ.), Kosuke Sasaki, Masakazu Moriguchi, Hisashi Noda (NECSI), Takashi Omori, Masahiko Osawa (Nihon Univ.) ET2023-46		 To reduce the burden on educators in inquiry-based learning, we realize a support system to deepen the mentee’s question... [more] ET2023-46
pp.5-9
HCS 2023-01-22
16:25		 Kyoto Kyoto Institute of Technology
(Primary: On-site, Secondary: Online)		 Testing of Mentalization Using a Chat System with Semi-Automatic Question Generation
Kosuke Sasaki (NEC Solution Innovators/Nihon Univ.), Shota Tatarai (Nihon Univ.), Masakazu Moriguchi, Hisashi Noda (NEC Solution Innovators), Takashi Omori, Akihiro Miyata, Osawa Masahiko (Nihon Univ.) HCS2022-75		  [more] HCS2022-75
pp.112-117
MBE, NC 2022-12-03
09:55		 Osaka Osaka Electro-Communication University Hyperbolic Embedding for Out of Distribution
Shota Tatarai, Yuta Ashihara, Akihiro MIyata, Masahiko Osawa (Nihon Univ.) MBE2022-30 NC2022-52		  [more] MBE2022-30 NC2022-52
pp.32-37
HCGSYMPO
(2nd)		 2021-12-15
- 2021-12-17		 Online Online Empathy Process Inspired Complementary Learning Method for Mind Model of Self and Others
Kosuke Sasaki (Nihon Univ.), Hayato Oikawa, Shota Tatarai (Senshu Univ.), Akihiro Miyata, Takashi Omori, Masahiko Osawa (Nihon Univ.) 		Human beings learn to build relationships with others by combining others mind model with self mind model.
On the other... [more]
MBE, NC, NLP, CAS
(Joint) [detail]		 2020-10-30
17:35		 Online Online Hyperbolic Space Embedding for Open Set Recognition
Shota Tatarai (Senshu Univ.), Yuta Ashihara (Nihon Univ/Glia Computing Co.,Ltd.), Kenji Aoki (Glia Computing Co.,Ltd.), Masahiko Osaawa (Nihon Univ./Senshu Univ.) NC2020-27		 Many of deep learning algorithms perform well when the training and testing data are sampled from the
same class space.... [more]		 NC2020-27
pp.100-105
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