Hiroshi Tsukimoto

	2004
15		Hiroshi Tsukimoto, Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi: Nonparametric regression analysis of functional brain images. Systems and Computers in Japan 35(1): 67-78 (2004)
	2003
14		Hiroshi Tsukimoto, Hisaaki Hatano: The functional localization of neural networks using genetic algorithms. Neural Networks 16(1): 55-67 (2003)
	2002
13		Hiroshi Tsukimoto, Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi: Rule Discovery from fMRI Brain Images by Logical Regression Analysis. Progress in Discovery Science 2002: 232-245
	2001
12		Hiroshi Tsukimoto: Pattern reasoning: Logical reasoning of neural networks. Systems and Computers in Japan 32(2): 1-10 (2001)
	2000
11		Hiroshi Tsukimoto, Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi, Eiko Hatakeyama, Yoshifumi Miyazaki: Knowledge Discovery from fMRI Brain Images by Logical Regression Analysis. Discovery Science 2000: 212-224
10		Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi, Hiroshi Tsukimoto: Data Mining from Functional Brain Images. MDM/KDD 2000: 91-97
	1999
9		Hiroshi Tsukimoto: Rule Extraction from Prediction Models. PAKDD 1999: 34-43
	1998
8		Hiroshi Tsukimoto, Chie Morita: The Discovery of Rules from Brain Images. Discovery Science 1998: 198-209
7		Chie Morita, Hiroshi Tsukimoto: Knowledge discovery from numerical data. Knowl.-Based Syst. 10(7): 413-419 (1998)
	1997
6		Hiroshi Tsukimoto: Extracting Propositions from Trained Neural Networks. IJCAI 1997: 1098-1105
5		Hiroshi Tsukimoto, Chie Morita, Nobuhiro Shimogori: An inductive learning algorithm based on regression analysis. Systems and Computers in Japan 28(3): 62-70 (1997)
	1996
4		Chie Morita, Hiroshi Tsukimoto: Knowledge Discovery from Numerical Data. IEA/AIE 1996: 425-430
	1994
3		Hiroshi Tsukimoto: The Discovery of Logical Propositions in Numerical Data. KDD Workshop 1994: 205-216
2		Hiroshi Tsukimoto, Chie Morita: The Discovery of Propositions in Noisy Data. Machine Intelligence 13 1994: 143-167
	1993
1		Hiroshi Tsukimoto, Chie Morita: Efficient algorithms for inductive learning - an application of multi-linear functions to inductive learning. Machine Intelligence 14 1993: 435-

Coauthor Index

1	Eiko Hatakeyama	[11]
2	Hisaaki Hatano	[14]
3	Mitsuru Kakimoto	[10] [11] [13] [15]
4	Yoshiaki Kikuchi	[10] [11] [13] [15]
5	Yoshifumi Miyazaki	[11]
6	Chie Morita	[1] [2] [4] [5] [7] [8] [10] [11] [13] [15]
7	Nobuhiro Shimogori	[5]

Colors in the list of coauthors