Hiroyuki Narihisa

	2008
21		Hirotaka Inoue, Hiroyuki Narihisa: Efficient Incremental Learning with Self-Organizing Neural Grove. DMIN 2008: 578-582
	2007
20		Kengo Katayama, Masashi Sadamatsu, Hiroyuki Narihisa: Iterated k-Opt Local Search for the Maximum Clique Problem. EvoCOP 2007: 84-95
19		Hirotaka Inoue, Hiroyuki Narihisa: Efficient Incremental Learning Using Self-Organizing Neural Grove. ICONIP (1) 2007: 762-770
18		Kengo Katayama, Hiroshi Yamashita, Hiroyuki Narihisa: Variable depth search and iterated local search for the node placement problem in multihop WDM lightwave networks. IEEE Congress on Evolutionary Computation 2007: 3508-3515
	2005
17		Hiroyuki Narihisa, Takahiro Taniguchi, Michiaki Thuda, Kengo Katayama: Efficiency of Parallel Exponential Evolutionary Programming. ICPP Workshops 2005: 588-595
16		Hirotaka Inoue, Hiroyuki Narihisa: Self-organizing neural grove: effective multiple classifier system with pruned self-generating neural trees. ISCAS (3) 2005: 2502-2505
15		Kengo Katayama, Takahiro Koshiishi, Hiroyuki Narihisa: Reinforcement learning agents with primary knowledge designed by analytic hierarchy process. SAC 2005: 14-21
14		Kengo Katayama, Akihiro Hamamoto, Hiroyuki Narihisa: An effective local search for the maximum clique problem. Inf. Process. Lett. 95(5): 503-511 (2005)
13		Hirotaka Inoue, Hiroyuki Narihisa: Parallel performance of ensemble self-generating neural networks for chaotic time series prediction problems. Systems and Computers in Japan 36(10): 82-92 (2005)
	2004
12		Hirotaka Inoue, Hiroyuki Narihisa: Self-organizing Neural Grove: Efficient Multiple Classifier System Using Pruned Self-generating Neural Trees. PPSN 2004: 1113-1122
11		Kengo Katayama, Akihiro Hamamoto, Hiroyuki Narihisa: Solving the maximum clique problem by k-opt local search. SAC 2004: 1021-1025
	2003
10		Hirotaka Inoue, Hiroyuki Narihisa: Effective Pruning Method for a Multiple Classifier System Based on Self-Generating Neural Networks. ICANN 2003: 11-18
9		Hirotaka Inoue, Hiroyuki Narihisa: Improving Performance of a Multiple Classifier System Using Self-generating Neural Networks. Multiple Classifier Systems 2003: 256-265
	2002
8		Hirotaka Inoue, Hiroyuki Narihisa: Optimizing a Multiple Classifier System. PRICAI 2002: 285-294
	2001
7		Hirotaka Inoue, Yoshinobu Fukunaga, Hiroyuki Narihisa: Efficient Hybrid Neural Network for Chaotic Time Series Prediction. ICANN 2001: 712-718
6		Hirotaka Inoue, Hiroyuki Narihisa: Parallel and Distributed Mining with Ensemble Self-Generating Neural Networks. ICPADS 2001: 423-428
	2000
5		Kengo Katayama, Masafumi Tani, Hiroyuki Narihisa: Solving Large Binary Quadratic Programming Problems by Effective Genetic Local Search Algorithm. GECCO 2000: 643-650
4		Hirotaka Inoue, Hiroyuki Narihisa: Predicting Chaotic Time Series by Ensemble Self-Generating Neural Networks. IJCNN (2) 2000: 231-236
3		Hirotaka Inoue, Hiroyuki Narihisa: Improving Generalization Ability of Self-Generating Neural Networks Through Ensemble Averaging. PAKDD 2000: 177-180
	1999
2		Kengo Katayama, Hiroyuki Narihisa: A New Iterated Local Search Algorithm Using Genetic Crossover for the Traveling Salesman Problem. SAC 1999: 302-306
1		Kengo Katayama, Hisayuki Hirabayashi, Hiroyuki Narihisa: Performance analysis for crossover operators of genetic algorithm. Systems and Computers in Japan 30(2): 20-30 (1999)

Coauthor Index

1	Yoshinobu Fukunaga	[7]
2	Akihiro Hamamoto	[11] [14]
3	Hisayuki Hirabayashi	[1]
4	Hirotaka Inoue	[3] [4] [6] [7] [8] [9] [10] [12] [13] [16] [19] [21]
5	Kengo Katayama	[1] [2] [5] [11] [14] [15] [17] [18] [20]
6	Takahiro Koshiishi	[15]
7	Masashi Sadamatsu	[20]
8	Masafumi Tani	[5]
9	Takahiro Taniguchi	[17]
10	Michiaki Thuda	[17]
11	Hiroshi Yamashita	[18]

Colors in the list of coauthors