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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
SR 2024-01-25
10:30		 Nagano Nagano-ken JA building
(Primary: On-site, Secondary: Online)		 A Certification of Channel Model Measurement Methods for Local 5G Systems in Communication Environments of Japan and German
Takashi Shiba, Tomoyuki Furuichi (Tohoku Univ.), Gustavo Cainelli, Bodo Gambal (IFAK), Sven Müller, Nils Kranefeld, Giuliano Persico (DEMAG), Lisa Underberg (IFAK), Noriharu Suematsu (Tohoku Univ.) SR2023-69		 We have already confirmed our PDP (Power Delay Profile) measurement method without Tx special demodulation for Local 5G ... [more] SR2023-69
pp.1-8
SIP, EA, SP, MI
(Joint) [detail]		 2018-03-19
13:00		 Okinawa   [Poster Presentation] Tolerance of local linear predictive coding against disturbance noise
Fumihiko Ishiyama (NTT) EA2017-123 SIP2017-132 SP2017-106		 We are investigating countermeasure technique against electro-magnetic noise by using the method based on the linear pre... [more] EA2017-123 SIP2017-132 SP2017-106
pp.127-132
IBISML 2013-03-05
16:30		 Aichi Nagoya Institute of Technology Similarity adaptation for label propagation based on local linear reconstruction
Masayuki Karasuyama, Hiroshi Mamitsuka (Kyoto Univ.) IBISML2012-109		 Label propagation is one of the state-of-the-art methods for semi-supervised
learning,
which estimates labels by pro... [more]		 IBISML2012-109
pp.115-121
IBISML 2012-11-07
15:30		 Tokyo Bunkyo School Building, Tokyo Campus, Tsukuba Univ. Fast Gaussian Process Regression using hash function
Yuya Okadome, Yutaka Nakamura, Hiroshi Ishiguro (Osaka Univ.) IBISML2012-55		 A Gaussian Process Regression (GPR) has ability to deal with a non-linear regression easily.
However, the calculation c... [more]		 IBISML2012-55
pp.151-155
NLP 2008-01-31
13:50		 Hokkaido   Nonlinear Prediction for Top and Bottom Values of Time Series
Masaki Ota, Tomoya Suzuki (Doshisha Univ.) NLP2007-131		 To predict stock price and foreign exchange rates, it is efficient to follow only these top and bottom values more than ... [more] NLP2007-131
pp.13-18
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