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Committee Date Time Place Paper Title / Authors Abstract Paper #
RCS, SR, SRW
(Joint)		 2021-03-05
16:55		 Online Online Electromagnetic Noise Classification and Novelty Detection for Frequency Sharing among Various Communications in the Manufacturing Field
Michio Miyamoto, Ayano Ohnishi, Yoshio Takeuchi (ATR), Toshiyuki Maeyama (ATR/Takushoku Univ.), Akio Hasegawa, Hiroyuki Yokoyama (ATR) SR2020-89		 Machine learning is applied to classify the electromagnetic noise generated in the manufacturing field. The frequency an... [more] SR2020-89
pp.99-103
ICSS, IPSJ-SPT 2016-03-04
10:00		 Kyoto Academic Center for Computing and Media Studies, Kyoto University A fast detecting method for obfuscated malicious JavaScript based on text pattern analysis
Jiawei Su, Katsunari Yoshioka, Junji Shikata, Tsutomu Matsumoto (YNU) ICSS2015-58		 The malicious JavaScript is a common springboard for attackers to launch several types of network attacks, such as Drive... [more] ICSS2015-58
pp.65-70
IT 2010-11-30
14:30		 Nagano   [Invited Talk] Recent Advances in Information-Theoretic Learning Theory -- Tracking Latent Dynamics --
Kenji Yamanishi (Univ. of Tokyo) IT2010-51		 This paper addresses the issue of detecting changes of latent strucures behind data.The theory of probabilsitic models w... [more] IT2010-51
pp.1-8
NC, MBE
(Joint)		 2009-11-12
15:20		 Miyagi Tohoku Univ. Numerical Experiment of Sequence Learning Model with Novelty Detection
Yutaro Innami, Toshiya Iwai (Nihon Univ.) NC2009-58		 We propose a sequential learning model with following functions, taking account of both assumptions and experimental evi... [more] NC2009-58
pp.47-52
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