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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 #
R 2019-07-26
14:25		 Iwate Ichinoseki Cultural Center A study on asymptotically unbiased estimators of an FGM copula
Shuhei Ota (Kanagawa Univ.), Mitsuhiro Kimura (Hosei Univ.) R2019-15		 A copula, one of the multivariate distributions, is known as a useful tool for dependence modeling because they can expr... [more] R2019-15
pp.7-12
IBISML 2017-03-07
11:30		 Tokyo Tokyo Institute of Technology A stochastic optimization method and generalization bounds for voting classifiers by continuous density functions
Atsushi Nitanda (Tokyo Tech./NTTDATA MSI), Taiji Suzuki (Tokyo Tech./JST/RIKEN) IBISML2016-108		 We consider a learning method for the majority vote classifier by probability measure on continuously parametrized space... [more] IBISML2016-108
pp.63-69
IBISML 2016-11-17
14:00		 Kyoto Kyoto Univ. [Poster Presentation] Stochastic Particle Gradient Descent for the Infinite Majority Vote Classifier
Atsushi Nitanda, Taiji Suzuki (Tokyo Tech.) IBISML2016-79		 We consider a learning method for the infinite majority vote classifier combined by a density on a continuous space of b... [more] IBISML2016-79
pp.235-241
EA, SIP 2007-05-25
11:00		 Osaka Osaka Univ. An adaptive howling canceller based on distance measurement
Akira Sogami, Arata Kawamura, Youji Iiguni (Osaka Univ.) EA2007-20 SIP2007-24		 We usually use a loudspeaker and a microphone at the speech and the concert and so on.
When we use them, howling someti... [more]		 EA2007-20 SIP2007-24
pp.15-20
COMP 2005-10-18
11:00		 Miyagi Tohoku Univ. Margin Preserving Projection with Limited Randomness and Embedding to Boolean Space
Tatsuya Watanabe, Eiji Takimoto, Kazuyuki Amano, Akira Maruoka (Tohoku Univ.) 		Learning large margin classifiers is one of the most important problems in machine learning.
However, it is hard to fin... [more]		 COMP2005-39
pp.21-28
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