Atsuyoshi Nakamura

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Name
Atsuyoshi Nakamura
URL
https://prml.main.ist.hokudai.ac.jp/nakamuraenglish/
Affiliation
Hokkaido University
Section
Graduate School of Information Science and Technology
Research funding number
50344487

Research Areas

 
 

Academic & Professional Experience

 
Jul 2002
 - 
Today
Associate Professor, Graduate School of Information Science and Technology, Hokkaido University
 
Apr 1988
 - 
Jun 2002
NEC Corporation
 

Education

 
Apr 1986
 - 
Mar 1988
Tokyo Institute of Technology
 
Apr 1982
 - 
Mar 1986
Department of Information Science, School of Science, Tokyo Institute of Technology
 

Published Papers

 
Aurélien Pélissier, Atsuyoshi Nakamura, Koji Tabata
SIAM International Conference on Data Mining, SDM 2019   450-458   Jan 2019
Copyright © 2019 by SIAM. Monte Carlo tree search (MCTS) has received considerable interest due to its spectacular success in the difficult problem of computer Go and also proved beneficial in a range of other domains. A major issue that has recei...
Hideaki Kano,Junya Honda,Kentaro Sakamaki,Kentaro Matsuura,Atsuyoshi Nakamura,Masashi Sugiyama
Machine Learning   108(5) 721-745   2019   [Refereed]
Takashi Takemoto,Normann Mertig,Masato Hayashi,Saki Susa-Tanaka,Hiroshi Teramoto,Atsuyoshi Nakamura,Ichigaku Takigawa,Shin-ichi Minato,Tamiki Komatsuzaki,Masanao Yamaoka
2018 International Conference on ReConFigurable Computing and FPGAs, ReConFig 2018, Cancun, Mexico, December 3-5, 2018   1-8   2018   [Refereed]
Yuya Sugie,Array,Array,Array,Hiroshi Teramoto,Array,Array,Shin-ichi Minato,Masanao Yamaoka,Array
Theory and Practice of Natural Computing - 7th International Conference, TPNC 2018, Dublin, Ireland, December 12-14, 2018, Proceedings   111-123   2018   [Refereed]
Ryo Watanabe,Junpei Komiyama,Atsuyoshi Nakamura,Mineichi Kudo
IEICE Transactions   101-A(3) 662-667   2018   [Refereed]
Ryo Watanabe,Junpei Komiyama,Atsuyoshi Nakamura,Mineichi Kudo
IEICE Transactions   100-A(11) 2470-2486   2017   [Refereed]
Koji Tabata,Atsuyoshi Nakamura,Mineichi Kudo
IEICE Transactions   100-D(5) 994-1002   2017   [Refereed]
Shunsuke Suzuki,Mineichi Kudo,Atsuyoshi Nakamura
IEEE International Conference on Identity, Security and Behavior Analysis, ISBA 2016, Sendai, Japan, February 29 - March 2, 2016   1-6   2016   [Refereed]
Atsuyoshi Nakamura,David P. Helmbold,Manfred K. Warmuth
Language and Automata Theory and Applications - 10th International Conference, LATA 2016, Prague, Czech Republic, March 14-18, 2016, Proceedings   412-423   2016   [Refereed]
Atsuyoshi Nakamura,Ichigaku Takigawa,Hisashi Tosaka,Mineichi Kudo,Hiroshi Mamitsuka
Discrete Applied Mathematics   200 123-152   2016   [Refereed]
Koji Tabata,Atsuyoshi Nakamura,Mineichi Kudo
Discovery Science - 18th International Conference, DS 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings   275-283   2015   [Refereed]
Ryo Watanabe,Atsuyoshi Nakamura,Mineichi Kudo
Oper. Res. Lett.   43(6) 558-563   2015   [Refereed]
Ayako Mikami,Mineichi Kudo,Atsuyoshi Nakamura
Multiple Classifier Systems - 12th International Workshop, MCS 2015, Günzburg, Germany, June 29 - July 1, 2015, Proceedings   27-37   2015   [Refereed]
Atsuyoshi Nakamura
Proceedings of the Sixth Asian Conference on Machine Learning, ACML 2014, Nha Trang City, Vietnam, November 26-28, 2014.      2014   [Refereed]
Hiroyuki Hanada,Mineichi Kudo,Atsuyoshi Nakamura
Theor. Comput. Sci.   530 23-41   2014   [Refereed]
Koji Ouchi,Atsuyoshi Nakamura,Mineichi Kudo
Pattern Recognition   47(3) 1459-1468   2014   [Refereed]
Atsuyoshi Nakamura,Tomoya Saito,Ichigaku Takigawa,Mineichi Kudo,Hiroshi Mamitsuka
Discrete Applied Mathematics   161(10-11) 1556-1575   2013   [Refereed]
Koji Tabata, Atsuyoshi Nakamura, Mineichi Kudo
Lecture Notes in Artificial Intelligence (DS2012)   7569 169-183   Oct 2012   [Refereed]
Koji Tabata,Atsuyoshi Nakamura,Mineichi Kudo
Discovery Science - 15th International Conference, DS 2012, Lyon, France, October 29-31, 2012. Proceedings   169-183   2012   [Refereed]
Takashi Saso,Kojiro Kobayashi,Atsuyoshi Nakamura
Inf. Process. Lett.   111(12) 595-599   2011   [Refereed]
Tetsuji Takahashi,Mineichi Kudo,Atsuyoshi Nakamura
Pattern Recognition Letters   32(16) 2224-2230   2011   [Refereed]
Hiroyuki Hanada,Atsuyoshi Nakamura,Mineichi Kudo
2011 IEEE International Conference on Granular Computing, GrC-2011, Kaohsiung, Taiwan, November 8-10, 2011   231-236   2011   [Refereed]
Koji Ouchi,Atsuyoshi Nakamura,Mineichi Kudo
2011 IEEE International Conference on Granular Computing, GrC-2011, Kaohsiung, Taiwan, November 8-10, 2011   533-538   2011   [Refereed]
Atsuyoshi Nakamura,Mineichi Kudo
Advances in Knowledge Discovery and Data Mining - 15th Pacific-Asia Conference, PAKDD 2011, Shenzhen, China, May 24-27, 2011, Proceedings, Part II   234-245   2011   [Refereed]
Taishi Uchiya,Atsuyoshi Nakamura,Mineichi Kudo
Algorithmic Learning Theory, 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings   375-389   2010   [Refereed]
Atsuyoshi Nakamura,Tomoya Saito,Ichigaku Takigawa,Hiroshi Mamitsuka,Mineichi Kudo
String Processing and Information Retrieval - 17th International Symposium, SPIRE 2010, Los Cabos, Mexico, October 11-13, 2010. Proceedings   185-190   2010   [Refereed]
Ichigaku Takigawa,Mineichi Kudo,Atsuyoshi Nakamura
Eng. Appl. of AI   22(1) 101-108   2009   [Refereed]
Tetsuji Takahashi,Mineichi Kudo,Atsuyoshi Nakamura
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009, Guadalajara, Jalisco, Mexico, November 15-18, 2009. Proceedings   441-448   2009   [Refereed]
Satoshi Shirai,Mineichi Kudo,Atsuyoshi Nakamura
Multiple Classifier Systems, 8th International Workshop, MCS 2009, Reykjavik, Iceland, June 10-12, 2009. Proceedings   22-31   2009   [Refereed]
Yohji Shidara,Mineichi Kudo,Atsuyoshi Nakamura
Trans. MLDM   1(1) 17-30   2008   [Refereed]
Atsuyoshi Nakamura,Mineichi Kudo
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), December 15-19, 2008, Pisa, Italy   482-491   2008   [Refereed]
Mineichi Kudo,Atsuyoshi Nakamura,Ichigaku Takigawa
19th International Conference on Pattern Recognition (ICPR 2008), December 8-11, 2008, Tampa, Florida, USA   1-4   2008   [Refereed]
Yohji Shidara,Mineichi Kudo,Atsuyoshi Nakamura
19th International Conference on Pattern Recognition (ICPR 2008), December 8-11, 2008, Tampa, Florida, USA   1-4   2008   [Refereed]
Satoshi Shirai,Mineichi Kudo,Atsuyoshi Nakamura
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings   801-810   2008   [Refereed]
Hisashi Tosaka,Atsuyoshi Nakamura,Mineichi Kudo
Discovery Science, 10th International Conference, DS 2007, Sendai, Japan, October 1-4, 2007, Proceedings   286-290   2007   [Refereed]
Yohji Shidara,Atsuyoshi Nakamura,Mineichi Kudo
Machine Learning and Data Mining in Pattern Recognition, 5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007, Proceedings   490-498   2007   [Refereed]
Atsuyoshi Nakamura
Algorithmic Learning Theory, 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings   378-392   2006   [Refereed]
Atsuyoshi Nakamura,Naoki Abe
Electronic Commerce Research   5(1) 75-98   2005   [Refereed]
Atsuyoshi Nakamura
Inf. Comput.   201(2) 178-198   2005   [Refereed]
Atsuyoshi Nakamura,Michael Schmitt,Niels Schmitt,Hans-Ulrich Simon
Journal of Machine Learning Research   6 1383-1403   2005   [Refereed]
Mineichi Kudo,Atsuyoshi Nakamura
Federation over the Web - International Workshop, Dagstuhl Castle, Germany, May 1-6, 2005. Revised Selected Papers   79-96   2005   [Refereed]
Hidehiko Ino,Mineichi Kudo,Atsuyoshi Nakamura
ICDE Workshops 2005   1257   2005   [Refereed]
Hiroyuki Hasegawa,Mineichi Kudo,Atsuyoshi Nakamura
Knowledge-Based Intelligent Information and Engineering Systems, 9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings, Part IV   668-674   2005   [Refereed]
Ichigaku Takigawa,Mineichi Kudo,Atsuyoshi Nakamura
Machine Learning and Data Mining in Pattern Recognition, 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings   90-99   2005   [Refereed]
Atsuyoshi Nakamura,Mineichi Kudo
Advances in Knowledge Discovery and Data Mining, 9th Pacific-Asia Conference, PAKDD 2005, Hanoi, Vietnam, May 18-20, 2005, Proceedings   850-860   2005   [Refereed]
Hidehiko Ino,Mineichi Kudo,Atsuyoshi Nakamura
Proceedings of the 14th international conference on World Wide Web, WWW 2005, Chiba, Japan, May 10-14, 2005   661-669   2005   [Refereed]
Yohji Shidara,Mineichi Kudo,Atsuyoshi Nakamura
Foundations of Data Mining and knowledge Discovery   161-170   2005   [Refereed]
Atsuyoshi Nakamura,Michael Schmitt,Niels Schmitt,Hans-Ulrich Simon
Learning Theory, 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings   518-533   2004   [Refereed]
Ichigaku Takigawa,Mineichi Kudo,Atsuyoshi Nakamura,Jun Toyama
Independent Component Analysis and Blind Signal Separation, Fifth International Conference, ICA 2004, Granada, Spain, September 22-24, 2004, Proceedings   193-200   2004   [Refereed]
Atsuyoshi Nakamura,Mineichi Kudo,Akira Tanaka,Kazuhiko Tanabe
Discovery Science, 6th International Conference, DS 2003, Sapporo, Japan, October 17-19,2003, Proceedings   393-401   2003   [Refereed]
Atsuyoshi Nakamura,Mineichi Kudo,Akira Tanaka
Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings   339-349   2003   [Refereed]
Atsuyoshi Nakamura,Naoki Abe
J. Comput. Syst. Sci.   65(2) 224-256   2002   [Refereed]
Atsuyoshi Nakamura
Proceedings of the Eleventh International World Wide Web Conference, WWW 2002, May 7-11, 2002, Honolulu, Hawaii   536-541   2002   [Refereed]
Atsuyoshi Nakamura
Theor. Comput. Sci.   241(1-2) 83-114   2000   [Refereed]
Atsuyoshi Nakamura,Naoki Abe,Hiroshi Matoba,Katsuhiro Ochiai
Proceedings of the 8th ACM International Conference on Multimedia 2000, Los Angeles, CA, USA, October 30 - November 3, 2000.   57-66   2000   [Refereed]
Marc Langheinrich,Atsuyoshi Nakamura,Naoki Abe,Tomonari Kamba,Yoshiyuki Koseki
Computer Networks   31(11-16) 1259-1272   1999   [Refereed]
Atsuyoshi Nakamura
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, COLT 1999, Santa Cruz, CA, USA, July 7-9, 1999   215-225   1999   [Refereed]
Naoki Abe,Atsuyoshi Nakamura
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999   12-21   1999   [Refereed]
Atsuyoshi Nakamura,Jun-ichi Takeuchi,Naoki Abe
Ann. Math. Artif. Intell.   23(1-2) 53-82   1998   [Refereed]
Naoki Abe,Hiroshi Mamitsuka,Atsuyoshi Nakamura
Discovery Science, First International Conference, DS '98, Fukuoka, Japan, December 14-16, 1998, Proceedings   387-388   1998   [Refereed]
Atsuyoshi Nakamura,Naoki Abe
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998   395-403   1998   [Refereed]
Atsuyoshi Nakamura
Algorithmic Learning Theory, 8th International Conference, ALT '97, Sendai, Japan, October 6-8, 1997, Proceedings   307-322   1997   [Refereed]
Atsuyoshi Nakamura
Algorithmic Learning Theory, 7th International Workshop, ALT '96, Sydney, Australia, October 23-25, 1996, Proceedings   37-50   1996   [Refereed]
Atsuyoshi Nakamura,Naoki Abe
Theor. Comput. Sci.   137(1) 159-176   1995   [Refereed]
Atsuyoshi Nakamura,Shinji Miura
Algorithmic Learning Theory, 6th International Conference, ALT '95, Fukuoka, Japan, October 18-20, 1995, Proceedings   138-150   1995   [Refereed]
Atsuyoshi Nakamura,Naoki Abe
Proceedings of the Eigth Annual Conference on Computational Learning Theory, COLT 1995, Santa Cruz, California, USA, July 5-8, 1995   214-221   1995   [Refereed]
Naoki Abe,Hang Li,Atsuyoshi Nakamura
Machine Learning, Proceedings of the Twelfth International Conference on Machine Learning, Tahoe City, California, USA, July 9-12, 1995   3-11   1995   [Refereed]
Naoki Abe,Hang Li,Atsuyoshi Nakamura
CoRR   abs/cmp-lg/9507010    1995   [Refereed]
Atsuyoshi Nakamura,Naoki Abe,Jun-ichi Takeuchi
Algorithmic Learning Theory, 4th International Workshop on Analogical and Inductive Inference, AII '94, 5th International Workshop on Algorithmic Learning Theory, ALT '94, Reinhardsbrunn Castle, Germany, October 10-15, 1994, Proceedings   500-515   1994   [Refereed]
Atsuyoshi Nakamura,Naoki Abe
Algorithmic Learning Theory, 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993, Proceedings   300-313   1993   [Refereed]

Misc

 
櫻田 健斗, 中村 篤祥
人工知能基本問題研究会   109 62-67   Mar 2019
中村篤祥, ペリシエ オレリアン, 田畑公次, 小松崎民樹
日本細胞生物学会大会(Web)   71st ROMBUNNO.1SEp‐07 (WEB ONLY)   2019
田畑公次, 中村篤祥, 小松崎民樹
電子情報通信学会技術研究報告   118(284(IBISML2018 44-104)(Web)) 353‐360 (WEB ONLY)   Oct 2018
田畑 公次, 中村 篤祥, 本多 淳也, 小松崎 民樹
人工知能基本問題研究会   106 94-99   Mar 2018
Aurelien Pelissier,Atsuyoshi Nakamura,Koji Tabata
CoRR   abs/1811.07531    2018
安井拓未, 中村篤祥, 中村篤祥, 田中章, 田中章, 工藤峰一, 工藤峰一
情報処理学会研究報告(Web)   2017(MUS-116) Vol.2017‐MUS‐116,No.15,1‐4 (WEB ONLY)   Aug 2017
中村 篤祥
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   117(110) 49-54   Jun 2017
中村 篤祥
人工知能基本問題研究会   103 45-50   Mar 2017
渡辺 僚, 中村 篤祥, 工藤 峰一
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   115(323) 167-174   Nov 2015
Helmbold David P., Nakamura Atsuyoshi, Warmuth Manfred K.
人工知能基本問題研究会   98 16-21   Aug 2015
中村 篤祥
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   115(112) 81-86   Jun 2015
TABATA Koji, NAKAMURA Atsuyoshi, KUDO Mineichi
IEICE technical report. Theoretical foundations of Computing   111(256) 7-14   Oct 2011
The Closeness Centrality is one of centrality measures of a node in a graph. It is calculated as the reciprocal of the sum of distances to all other nodes. In this paper, we propose a fast approximate algorithm that finds the node to maximize its ...
82 1-6   Aug 2011
OUCHI Koji, NAKAMURA Atsuyoshi, KUDO Mineichi
IEICE technical report   110(265) 99-104   Oct 2010
Blumer et al. showed that the class of concepts represented by finite unions of hyper-rectangles in d-dimensional Euclidean space is polynomial-time PAC learnable for a fixed natural number d. In their proof, they constructed an algorithm which co...
UCHIYA Taishi, NAKAMURA Atsuyoshi, KUDO Mineichi
IEICE technical report. Theoretical foundations of Computing   109(195) 13-20   Sep 2009
Adversarial bandit problems studied by Auer et al. are the multi-armed bandit problems in which no stochastic assumption is made on the nature of the process generating the rewards for actions. In this paper, we extend their theories to those in t...
TAKAHASHI Tetsuji, KUDO Mineichi, NAKAMURA Astuhiro
Technical report of IEICE. PRMU   108(363) 37-41   Dec 2008
It is an efficient way to approximate a class region by convex hulls of samples. However, the convex hull is computationally hard to be constructed in high dimensions. In this paper, we propose a way to construct an approximate convex hull in a li...
UCHIYA Taishi, NAKAMURA Atsuyoshi, KUDO Mineichi
Technical report of IEICE. PRMU   108(363) 213-218   Dec 2008
The multiarmed bandit problem is a problem in which a gambler chooses one arm of K nonidentical slot machines to play in a sequence of trials so as to maximize his reward. Past solutions for the bandit problem have almost always relied on assumpti...
NAKAMURA Atsuyoshi, KUDO Mineichi
IEICE technical report. Theoretical foundations of Computing   108(237) 9-16   Oct 2008
We propose packing alignment as an alignment for sequences of lengthened symbols like musical notes. Furthermore, we consider sequences of symbols with length and end position as a model of a general musical piece in which notes can overlap, and w...
NAKAMURA Atsuyoshi, KUDO Mineichi
IEICE technical report. Theoretical foundations of Computing   107(219) 35-42   Sep 2007
Representing a complicated region by union of simple regions is often preferred in various study areas because each component simple region is easy to understand and easy to deal with. Kudo et al. [2], [4] considered the following problem called s...
TOSAKA Hisashi, NAKAMURA Atsuyoshi, KUDO Mineichi
IEICE technical report. Data engineering   107(114) 7-12   Jun 2007
We study a novel problem of mining subtrees with frequent occurrence of similar subtrees, and propose an efficient algorithm for this problem. According to our problem setting, frequency of a subtree is counted not only for equivalent subtrees but...
TOSAKA Hisashi, NAKAMURA Atsuyoshi, KUDO Mineichi
Technical report of IEICE. PRMU   107(115) 7-12   Jun 2007
We study a novel problem of mining subtrees with frequent occurrence of similar subtrees, and propose an efficient algorithm for this problem. According to our problem setting, frequency of a subtree is counted not only for equivalent subtrees but...
Saito Tomoya, Nakamura Atsuyoshi, Kudo Mineichi
5(0) 1-4   Aug 2006
NAKAMURA Atsuyoshi
IEICE technical report. Theoretical foundations of Computing   105(273) 49-53   Sep 2005
In this paper, we study how easy to learn the class of linear ranking functions from n-dimensional Euclidean space to {1, 2, …, k}. We show its graph dimension, which is considered to indicate how easy to learn, is Θ(n+k). This graph dimension is ...
Nakamura Atsuyoshi, Shigezumi Takeya, Yamamoto Masaki
RIMS Kokyuroku   1426(0) 71-77   Apr 2005
KAWATA Takehiro, KUDO Mineichi, TOYAMA Jun, NAKAMURA Atsuyoshi
The transactions of the Institute of Electronics, Information and Communication Engineers. D-II   88(3) 629-635   Mar 2005
NAKAMURA Atsuyoshi, KUDO Mineichi
IPSJ SIG Notes   2004(101) 67-74   Oct 2004
In this paper, we propose an efficient algorithm enumerating all frequent subtrees containing all special nodes that are guaranteed to be included in all trees belonging to a given data. Our algorithm is a modification of TreeMiner algorithm [9] s...
NAKAMURA Atsuyoshi, KUDO Mineichi
IEICE technical report. Theoretical foundations of Computing   104(339) 7-14   Oct 2004
In this paper, we propose an efficient algorithm enumerating all frequent subtrees containing all special nodes that are guaranteed to be included in all trees belonging to a given data. Our algorithm is a modification of TreeMiner algorithm [9] s...
SHIDARA Yohji, NAKAMURA Atsuyoshi, KUDO Mineichi
Technical report of IEICE. PRMU   103(295) 7-11   Sep 2003
The methods which extract rules from database are useful for mining because of their human-readable output. Various methods have been proposed which construct some accurate classifiers and extract the rules from these classifiers. However, these a...
KAWATA Takehiro, NAKAMURA Atsuyoshi, TOYAMA Jun, KUDO Mineichi
Technical report of IEICE. PRMU   103(295) 1-5   Sep 2003
The method of detecting the wrong characters and correction is proposed to improve recognition precision in character recognition. We pay attention to a technique in which N-gram probabilities are used, and propose a method which detects misspelle...
Nakamura Atsuyoshi
12(4) 401-410   Dec 2002
We explain automatic recommendation techniques by which computer systems can automatically select goods or documents preferred by each user based on his/her buying or accessing history. Especially, we focus on the collaborative filtering method us...
LANGHEINRICH Marc., KAMBA Tomonari, NAKAMURA Atsuyoshi
IPSJ Magazine   40(8) 807-812   Aug 1999
ABE Naoki, NAKAMURA Atsuyoshi
IPSJ Magazine   38(7) 575-582   Jul 1997
ABE Naoki, NAKAMURA Atsuyoshi
IPSJ Magazine   38(7) 558-561   Jul 1997
Nakamura Atsuyoshi, Mamitsuka Hiroshi, Toba Hiroyasu, Abe Naoki
第52回平成8年前期(1) 55-56   Mar 1996
Naoki Abe, Hang Li, Atsuyoshi Nakamura
Proc. of The 12th Int. Conf. on Machine Learning, 1995      Jul 1995
We consider the problem of learning a certain type of lexical semantic
knowledge that can be expressed as a binary relation between words, such as the
so-called sub-categorization of verbs (a verb-noun relation) and the compound
noun phrase relati...
Nakamura Atsuyoshi
IEICE technical report. Theoretical foundations of Computing   94(181) 93-102   Jul 1994
We study the learning problem in which the learner predicts the value of each entry of d-dimensional{0,1}-valued matrix one by one. According to the agent who selects the next prediction entry,we consider this problem in two different models,self-...
Nakamura Atsuyoshi
IEICE technical report. Theoretical foundations of Computing   93(249) 53-58   Sep 1993
We investigate PAC learnability of planar rectangles of arbitrary orientation.We show an algorithm which outputs a hypothesis rectangle consistent with given m examples in time Ο(ml ogm).Since the class of planar rectangles of arbitrary oprientati...
Nakamura Atsuyoshi
第46回平成5年前期(3) 35-36   Mar 1993

Research Grants & Projects

 
Ministry of Education, Culture, Sports, Science and Technology: Grants-in-Aid for Scientific Research(基盤研究(C))
Project Year: 2009 - 2011    Investigator(s): Atsuyoshi NAKAMURA
As a data-dependent complexity measure, we proposed data-dependent VC dimension of Sperner family, and in hyper-rectangle subclass problem, we developed a fast algorithm for datasets with small such VC dimension. We also empirically showed efficie...
Ministry of Education, Culture, Sports, Science and Technology: Grants-in-Aid for Scientific Research(基盤研究(C))
Project Year: 2006 - 2007    Investigator(s): Jun TOYAMA
1) Classification of Features: The knowledge that is necessary for judgments are not numerical score like a real number but rough categories. A new concept "granularity" based on the rough categories was introduced. We interpreted discrete data as...
Ministry of Education, Culture, Sports, Science and Technology: Grants-in-Aid for Scientific Research(基盤研究(B))
Project Year: 2002 - 2005    Investigator(s): Mineichi KUDO
In this study, we classified the scaling problems of pattern recognition tasks into three of the following. The results are shown below, respectively.1.Scaling problem as for data number : We have changed the problem setting from the problem to ac...