| 2008 |
| 21 | | Hirotaka Inoue,
Hiroyuki Narihisa:
Efficient Incremental Learning with Self-Organizing Neural Grove.
DMIN 2008: 578-582 |
| 2007 |
| 20 | EE | Kengo Katayama,
Masashi Sadamatsu,
Hiroyuki Narihisa:
Iterated k-Opt Local Search for the Maximum Clique Problem.
EvoCOP 2007: 84-95 |
| 19 | EE | Hirotaka Inoue,
Hiroyuki Narihisa:
Efficient Incremental Learning Using Self-Organizing Neural Grove.
ICONIP (1) 2007: 762-770 |
| 18 | EE | 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 | EE | Hiroyuki Narihisa,
Takahiro Taniguchi,
Michiaki Thuda,
Kengo Katayama:
Efficiency of Parallel Exponential Evolutionary Programming.
ICPP Workshops 2005: 588-595 |
| 16 | EE | Hirotaka Inoue,
Hiroyuki Narihisa:
Self-organizing neural grove: effective multiple classifier system with pruned self-generating neural trees.
ISCAS (3) 2005: 2502-2505 |
| 15 | EE | Kengo Katayama,
Takahiro Koshiishi,
Hiroyuki Narihisa:
Reinforcement learning agents with primary knowledge designed by analytic hierarchy process.
SAC 2005: 14-21 |
| 14 | EE | Kengo Katayama,
Akihiro Hamamoto,
Hiroyuki Narihisa:
An effective local search for the maximum clique problem.
Inf. Process. Lett. 95(5): 503-511 (2005) |
| 13 | EE | 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 | EE | Hirotaka Inoue,
Hiroyuki Narihisa:
Self-organizing Neural Grove: Efficient Multiple Classifier System Using Pruned Self-generating Neural Trees.
PPSN 2004: 1113-1122 |
| 11 | EE | Kengo Katayama,
Akihiro Hamamoto,
Hiroyuki Narihisa:
Solving the maximum clique problem by k-opt local search.
SAC 2004: 1021-1025 |
| 2003 |
| 10 | EE | Hirotaka Inoue,
Hiroyuki Narihisa:
Effective Pruning Method for a Multiple Classifier System Based on Self-Generating Neural Networks.
ICANN 2003: 11-18 |
| 9 | EE | Hirotaka Inoue,
Hiroyuki Narihisa:
Improving Performance of a Multiple Classifier System Using Self-generating Neural Networks.
Multiple Classifier Systems 2003: 256-265 |
| 2002 |
| 8 | EE | Hirotaka Inoue,
Hiroyuki Narihisa:
Optimizing a Multiple Classifier System.
PRICAI 2002: 285-294 |
| 2001 |
| 7 | EE | 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 | EE | 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 | EE | Kengo Katayama,
Hiroyuki Narihisa:
A New Iterated Local Search Algorithm Using Genetic Crossover for the Traveling Salesman Problem.
SAC 1999: 302-306 |
| 1 | EE | Kengo Katayama,
Hisayuki Hirabayashi,
Hiroyuki Narihisa:
Performance analysis for crossover operators of genetic algorithm.
Systems and Computers in Japan 30(2): 20-30 (1999) |