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Committee Date Time Place Paper Title / Authors Abstract Paper #
ET 2020-03-07
11:25
Kagawa National Institute of Technology, Kagawa Collage
(Cancelled but technical report was issued)
A feasibility of performance assessment using a large scale data set of mutual evaluation
Minoru Nakayama (TokyoTech), Masaki Uto (UEC), Filippo Sciarrone (uniroma3), Marco Temperini (Sapienza) ET2019-79
Learning performance is often evaluated using a peer assessment setting such as MOOC environment. Their feasibility and ... [more] ET2019-79
pp.19-22
IBISML 2017-11-09
13:00
Tokyo Univ. of Tokyo [Poster Presentation] Learning huge Bayesian networks using RAI algorithm based on Bayes factor
Kazuki Natori, Masaki Uto, Maomi Ueno (UEC) IBISML2017-58
``Learning Bayesian networks'' has NP-hard problem. The state-of-the-arts method of learning Bayesian networks cannot le... [more] IBISML2017-58
pp.177-184
ET 2011-12-09
09:10
Shizuoka   Toulmin model based Argumentation Support System using Bayesian Network
Masaki Uto (UEC), Hiroaki Suzuki (Aoyama Gakuin Univ.), Maomi Ueno (UEC) ET2011-83
The purpose of this study is to develop a system which supports a persuasive argumentation. There are many related syste... [more] ET2011-83
pp.41-46
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