@article{journals/ijufks/InokuchiM06,
	title = {Kernel Methods for Clustering: Competitive Learning and C-Means.},
	author = {Ryo Inokuchi and Sadaaki Miyamoto},
	journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
	number = {4},
	pages = {481-493},
	url = {http://dblp.uni-trier.de/db/journals/ijufks/ijufks14.html#InokuchiM06},
	volume = {14},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/2ddd565ef72f6d6313d07d4b8634f18db/dblp},
	description = {dblp},
	ee = {http://dx.doi.org/10.1142/S0218488506004138}, date = {2008-07-09},
	keywords = {dblp }
}

@article{journals/ijufks/TorraNM06,
	title = {Editorial.},
	author = {Vicenç Torra and Yasuo Narukawa and Sadaaki Miyamoto},
	journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
	number = {4},
	pages = {369-370},
	url = {http://dblp.uni-trier.de/db/journals/ijufks/ijufks14.html#TorraNM06},
	volume = {14},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/29918012dcea12c00b3e87bc8a4e9e532/dblp},
	description = {dblp},
	ee = {http://dx.doi.org/10.1142/S0218488506004072}, date = {2008-07-09},
	keywords = {dblp }
}

@article{Kawai2005,
	title = {Carbon three-dimensional architecture formed by
                   intersectional collision of graphene patches},
	author = {Takazumi Kawai and Susumu Okada and Yoshiyuki Miyamoto and Atsushi Oshiyama},
	journal = {Physical Review B},
	number = {3},
	pages = {035428},
	publisher = {APS},
	url = {http://link.aps.org/abstract/PRB/v72/e035428},
	volume = {72},
	year = {2005},
	biburl = {http://www.bibsonomy.org/bibtex/228b7f9a794f68449c4fa7696ee0b6437/sansiro},
	collaboration = {}, eid = {035428}, numpages = {7}, serial = {005},
	keywords = {(chemical); binding bonds calculations; density dynamics energy; functional graphite; method; molecular stability theory; thermal tight-binding }
}

@article{Kawai2002,
	title = {{General Sum Rule for Chiral Index of Coalescing
                   Ultrathin Nanotubes}},
	author = {T. Kawai and Y. Miyamoto and O. Sugino and Y. Koga},
	journal = {Physical Review Letters},
	number = {8},
	pages = {85901},
	volume = {89},
	year = {2002},
	biburl = {http://www.bibsonomy.org/bibtex/234077c7cf221e179ec5e02f826a1d69c/sansiro},
	memo = {2006.07.28, search "kawai takazumi" in Google scholar,
                   pdf}, serial = {042},
	keywords = {imported }
}

@article{Kawai2002-b,
	title = {{Nanotube and nanohorn nucleation from graphitic
                   patches: Tight-binding molecular-dynamics simulations}},
	author = {T. Kawai and Y. Miyamoto and O. Sugino and Y. Koga},
	journal = {Physical Review B},
	number = {3},
	pages = {33404},
	volume = {66},
	year = {2002},
	biburl = {http://www.bibsonomy.org/bibtex/2de7f8e89660e5a46007accc7928f0855/sansiro},
	memo = {2006.07.28, search "kawai takazumi" in Google scholar,
                   pdf}, serial = {043},
	keywords = {imported }
}

@inproceedings{conf/fuzzIEEE/HamasunaEHM07,
	title = {Two Clustering Algorithms for Data with Tolerance based on Hard c-Means.},
	author = {Yukihiro Hamasuna and Yasunori Endo and Yasushi Hasegawa and Sadaaki Miyamoto},
	booktitle = {FUZZ-IEEE},
	crossref = {conf/fuzzIEEE/2007},
	pages = {1-4},
	publisher = {IEEE},
	url = {http://dblp.uni-trier.de/db/conf/fuzzIEEE/fuzzIEEE2007.html#HamasunaEHM07},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2d6a836f21d14e1217ee2778b09f021bc/dblp},
	description = {dblp},
	ee = {http://dx.doi.org/10.1109/FUZZY.2007.4295449}, date = {2008-07-04},
	keywords = {dblp }
}

@inproceedings{conf/mva/MiyamotoSU00,
	title = {Structural Stability Analysis for Texture Recognition.},
	author = {Yukinobu Miyamoto and Mahdad Nouri Shirazi and Kuniaki Uehara},
	booktitle = {MVA},
	crossref = {conf/mva/2000},
	pages = {275-278},
	url = {http://dblp.uni-trier.de/db/conf/mva/mva2000.html#MiyamotoSU00},
	year = {2000},
	biburl = {http://www.bibsonomy.org/bibtex/22b738bcc6030a24baaaf2045bffdc8ba/dblp},
	description = {dblp},
	ee = {http://b2.cvl.iis.u-tokyo.ac.jp/mva/proceedings/CommemorativeDVD/2000/papers/2000275.pdf}, isbn = {4-901122-00-2}, date = {2008-06-30},
	keywords = {dblp }
}

@inproceedings{conf/mva/MiyamotoKKI00,
	title = {Projective Differential Stereo Vision with Robust Segmentation by M-Estimation.},
	author = {Atsushi Miyamoto and Tsukasa Kondo and Shun'ichi Kaneko and Satoru Igarashi},
	booktitle = {MVA},
	crossref = {conf/mva/2000},
	pages = {471-475},
	url = {http://dblp.uni-trier.de/db/conf/mva/mva2000.html#MiyamotoKKI00},
	year = {2000},
	biburl = {http://www.bibsonomy.org/bibtex/2530780bceec8b1aca06320144ff3bc73/dblp},
	description = {dblp},
	ee = {http://b2.cvl.iis.u-tokyo.ac.jp/mva/proceedings/CommemorativeDVD/2000/papers/2000471.pdf}, isbn = {4-901122-00-2}, date = {2008-06-30},
	keywords = {dblp }
}

@inproceedings{conf/mdai/LimC05,
	title = {Language Generation for Conversational Agent by
                 Evolution of Plan Trees with Genetic Programming},
	address = {Tsukuba, Japan},
	author = {Sung-Soo Lim and Sung-Bae Cho},
	booktitle = {Modeling Decisions for Artificial Intelligence, Second
                 International Conference, MDAI 2005, Proceedings},
	editor = {Vicenc Torra and Yasuo Narukawa and Sadaaki Miyamoto},
	month = {July 25-27},
	pages = {305--315},
	publisher = {Springer},
	series = {Lecture Notes in Computer Science},
	volume = {3558},
	year = {2005},
	biburl = {http://www.bibsonomy.org/bibtex/25118ed7b668f1fd86b81d29330d020aa/brazovayeye},
	abstract = {As dialogue systems are widely demanded, the research
                 on natural language generation in dialogue has raised
                 interest. Contrary to conventional dialogue systems
                 that reply to the user with a set of predefined
                 answers, a newly developed dialogue system generates
                 them dynamically and trains answers to support more
                 flexible and customised dialogues with humans. The
                 paper proposes an evolutionary method for generating
                 sentences using interactive genetic programming.
                 Sentence plan trees, which stand for the sentence
                 structure, are adopted as the representation of genetic
                 programming. With interactive evolution process with
                 the user, a set of customized sentence structures is
                 obtained. The proposed method applies to a
                 dialogue-based travel planning system and the usability
                 test demonstrates the usefulness of the proposed
                 method},
	bibsource = {DBLP,
                 http://dblp.uni-trier.de/db/conf/mdai/mdai2005.html#HongC05}, size = {11 pages}, bibdate = {2005-07-18}, isbn = {3-540-27871-0}, doi = {doi:10.1007/11526018_30},
	keywords = {Dialogue Interactive Natural Sentence algorithms, generation, genetic language plan programming, system, tree }
}

@inproceedings{conf/mdai/HongC05,
	title = {Cancer Prediction Using Diversity-Based Ensemble
                 Genetic Programming},
	address = {Tsukuba, Japan},
	author = {Jin-Hyuk Hong and Sung-Bae Cho},
	booktitle = {Modeling Decisions for Artificial Intelligence, Second
                 International Conference, MDAI 2005, Proceedings},
	editor = {Vicenc Torra and Yasuo Narukawa and Sadaaki Miyamoto},
	month = {July 25-27},
	pages = {294--304},
	publisher = {Springer},
	series = {Lecture Notes in Computer Science},
	volume = {3558},
	year = {2005},
	biburl = {http://www.bibsonomy.org/bibtex/234b64f684b77b180bcc2fcf1e8d2c797/brazovayeye},
	abstract = {Combining a set of classifiers has often been
                 exploited to improve the classification performance.
                 Accurate as well as diverse base classifiers are
                 prerequisite to construct a good ensemble classifier.
                 Therefore, estimating diversity among classifiers has
                 been widely investigated. This paper presents an
                 ensemble approach that combines a set of diverse rules
                 obtained by genetic programming. Genetic programming
                 generates interpretable classification rules, and
                 diversity among them is directly estimated. Finally,
                 several diverse rules are combined by a fusion method
                 to generate a final decision. The proposed method has
                 been applied to cancer classification using gene
                 expression profiles, which is one of the important
                 issues in bioinformatics. Experiments on several
                 popular cancer datasets have demonstrated the usability
                 of the method. High performance of the proposed method
                 has been obtained, and the accuracy has increased by
                 diversity among the base classification rules.},
	bibsource = {DBLP,
                 http://dblp.uni-trier.de/db/conf/mdai/mdai2005.html#HongC05}, bibdate = {2005-07-18}, isbn = {3-540-27871-0}, doi = {doi:10.1007/11526018_29},
	keywords = {algorithms, genetic programming }
}