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Committee Date Time Place Paper Title / Authors Abstract Paper #
WBS, IT, ISEC 2021-03-05
10:15		 Online Online A Proposal for Causal Inference with Subjective Evaluation
Daichi Ikeda, Hikaru Morita (Graduate School of Kanagawa Univ.) IT2020-146 ISEC2020-76 WBS2020-65		 Machine learning techniques such as deep learning are often used for identification and personal matching in information... [more] IT2020-146 ISEC2020-76 WBS2020-65
pp.208-212
CQ, CBE
(Joint)		 2019-01-17
10:55		 Tokyo Tokyo Metropolitan Univ. User Behavior Analysis with Real Data Towards Micropayment Services
Yuka Sagisaka, Marat Zhanikeev (Tokyo Univ. of Science) CQ2018-77		 With rapid spread of various online video and audio streaming services, most of them depend on a continuous monthly paym... [more] CQ2018-77
pp.7-12
IN, NV
(Joint)		 2016-07-16
09:00		 Hokkaido Matsumaecho Sougo Center Analysis and Prediction of Popularity Dynamics of User Generated Contents
Tatsuya Tanaka (Osaka Univ.), Shingo Ata (Osaka City Univ.), Masayuki Murata (Osaka Univ.) IN2016-31		 In recent years, social networking services such as YouTube, which share UGC (User Generated Contents) have become much ... [more] IN2016-31
pp.49-54
PRMU, IBISML, IPSJ-CVIM [detail] 2014-09-01
17:00		 Ibaraki   Analysing the Fairness of Fairness-aware Classifiers
Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh (AIST), Jun Sakuma (Univ. of Tsukuba) PRMU2014-47 IBISML2014-28		 Calders and Verwer's two-naive-Bayes is one of fairness-aware classifiers, which classify objects while excluding the in... [more] PRMU2014-47 IBISML2014-28
pp.85-92
EE, IEE-HCA 2014-05-29
11:30		 Tokyo The Kikai Shinko Kaikan building Estimating on/off state of electric appliances by using statistical features of power-time-series -- Evaluating effectiveness of the feature, Evaluating estimation accuracy --
Hiroshi Inoue, Fumihiko Ishiyama, Toshio Watanabe, Takashi Ohyama (NTT) EE2014-4		 A method for estimating an On/Off state of air-conditioners using statistical features extracted from time series of ove... [more] EE2014-4
pp.19-23
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