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Committee Date Time Place Paper Title / Authors Abstract Paper #
NLP, MICT, MBE, NC
(Joint) [detail]		 2022-01-23
11:20		 Online Online Towards 2-class classification via e(m)-PCA
Jun Fujiki (Fukuoka Univ.), Shotaro Akaho (AIST) NC2021-43		 In many data analysis methods, observed data are treated as points in high-dimensional Euclidean space, called feature s... [more] NC2021-43
pp.55-58
WBS, IT, ISEC 2018-03-08
09:25		 Tokyo Katsusika Campas, Tokyo University of Science Information Geometrical Study of Cluster-Model Approximation for Boltzmann Machines
Kenta Toyoda, Tomohiro Ogawa (Univ. of Electro- Commu.) IT2017-104 ISEC2017-92 WBS2017-85		 In learning algorithms for Boltzmann machines, it is necessary but very hard to calculate the expectation of units with ... [more] IT2017-104 ISEC2017-92 WBS2017-85
pp.7-12
NC 2009-10-24
11:05		 Saga Saga University Learning of a Gibbs distribution from gene configurations in the genetic algorithm
Manabu Kitagata, Jun-ichi Inoue (Hokkaido Univ.) NC2009-45		 We introduce a learning algorithm of Gibbs distributions from training sets which are gene configurations generated by G... [more] NC2009-45
pp.47-52
PRMU, MI 2007-05-25
09:00		 Mie Mie Univ. Text Classification Method Based on Hierarchical Relations among Words
Katsuji Bessho, Toshio Uchiyama, Ryoji Kataoka (NTT) PRMU2007-15 MI2007-15		 Most of conventional text classification methods use symmetric measures such as cosine similarity or Euclidean metric of... [more] PRMU2007-15 MI2007-15
pp.79-84
NLC 2007-01-31
16:00		 Hokkaido Sapporo Convention Center Extraction of Hierarchical Relations among Words Based on Co-occurrences between Words and Semantic Attributes
Katsuji Bessho, Toshio Uchiyama, Ryoji Kataoka (NTT) 		The co-occurrence vectors that are the co-occurrence frequencies between words and semantic attributes in a corpus refle... [more] NLC2006-92
pp.31-36
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