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Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2018-11-05
15:10		 Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] A Fast Approximation of the Nadaraya-Watson Regression with the k-Nearest Neighbor Crossover Kernel
Toshio Ito, Naoki Hamada, Kotaro Ohori, Hiroyuki Higuchi (FUJITSU LAB) IBISML2018-46		 For a system with inputs and outputs, a nonparametric regression has been proposed to clarify the relationship between i... [more] IBISML2018-46
pp.17-21
IBISML 2017-11-09
13:00		 Tokyo Univ. of Tokyo Regression Method for Noisy Inputs based on Naradaya-Watson Estimator constructed from Noiseless Training Data
Ryo Hanafusa, Takeshi Okadome (Kwansei Gakuin Univ.) IBISML2017-46		 The regression method proposed in this paper produces a regression function for noisy inputs that minimizes the expected... [more] IBISML2017-46
pp.85-92
NC, IPSJ-BIO, IBISML, IPSJ-MPS
(Joint) [detail]		 2015-06-25
10:20		 Okinawa Okinawa Institute of Science and Technology e-Bagging: The Information Geometric Dual of Breiman's Bagging -- An Application to the Nadaraya-Watson Regression with the k-Nearest Neighbor Crossover Kernel --
Naoki Hamada, Hiroyuki Higuchi, Katsumi Homma (Fujitsu Labs.) IBISML2015-23		 The $k$-nearest neighbor crossover kernel, which we proposed recently, is a very flexible kernel that is virtually equiv... [more] IBISML2015-23
pp.187-194
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