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情報工学分野−人工知能(機械学習)に関する外部発表論文

最終更新日:2015/09/24

1.

Takashi Onoda.:Probabilistic Models based Intrusion Detection using Sequence Characteristics in Control System Communication,Proceedings of EANN 2014

2.

Takahiro Nishigaki,Takashi Onoda:Constrained Clustering Based on Semantic Information,The proceedings of TAAI 2013

3.

Takahiro Nishigaki,Takashi Onoda:Clustering based on independent component,Proceedings of International Conference on Web Intelligence

4.

M.Kiuchi, T.Onoda, "Intrusion Detection in Control System Communication based on Outlier Detection with One-class Classifier", SCIS & ISIS 2010, December 2010, Okayama Japan

5.

H.Murata, T.Onoda,S. Yamada(Natuinal Institute of Informatics),"A Kernel for Interactive Document Retrieval Based on Support Vector Machines", SCIS & ISIS 2010, December 2010, Okayama Japan

6.

小松秀徳,所 健一,篠原靖志:「遺伝的アルゴリズムを用いたヒートポンプ式給湯機の効率的な運転ルールの探索」,電気学会論文誌C, 130巻 2号,平成22年2月,pp194-200
【キーワード】ヒートポンプ式給湯機,運転ルール,遺伝的アルゴリズム

7.

F.Tsutsumi, H.Murata, T.Onoda, O.Oguri(Chubu Electric Power Co.,Inc.), H.Tanaka(Chubu Electric Power Co.,Inc.), "Automatic Corrosion Estimation Using Galvanized Steel Images on Power Transmission Towers", IEEE T&D Asia 2009, October 2009, Korea

8.

H. Murata,T. Onoda,S. Yamada (National Institute of Informatics), "SVM-Based Relevance Feedback Document Retrieval in Different Representations of Document Vectors,"Proceedings of the IASTED International Conference Artificial Intelligence and Applications 2009, pp. 100-105, Feb. 2009, Austria
【キーワード】Relevance Feedback, Document Retrieval, Active Learning, Support Vector Machines, Vector Representation, Rocchiobased System

9.

T. Onoda, N. Ito, H. Yamasaki (Kyushu Electric Power Co., Inc.), "Interactive Trouble Condition Sign Discovery for Hydroelectric Power Plants," International Conference on Neural Information Proceedings 2008, Nov. 2008, New Zealand

10.

篠原靖志,高須淳宏(国立情報学研究所):「効率的能動学習のための能動サポートカーネルマシン」 電子情報通信学会論文誌D, J91巻10号, 平成20年10月, pp. 2497-2506
【キーワード】サポートベクトルマシン,サポートカーネルマシン,能動学習

11.

M. Asari, N. Iyo, T. Onoda, Y. Nakano, K. Matsuda (Tohoku Electric Power Co., Inc.), M. Wada (Tohoku Electric Power Co., Inc.) M. Tamaki (Tohoku Instruments Co., Ltd.), "Method for Unferring Operating Status of Distributed Generator," ICEE 2008, July 2008, Okinawa
【キーワード】Distributed Generation, Distribution Networks, Operating Status, Power Factor, Support Vector Machine

12.

N. Sano, H. Suzuki (University of Tsukuba), M. Koda (University of Tsukuba), "A Robust Ensemble Learning Using Zero-One Loss Function," Journal of the Operations Research Society of Japan, Vol. 51 No. 1, March 2008
【キーワード】Data Analysis, Data Mining, Adaboost, Zero-One Loss Function, Stochastic

13.

T. Onoda, S. Yamada (National Institute of Informatics), "SVM-based Interactive Document Retrieval with Active Learning," New Generation Computing, Vol. 26 No. 1, 2008
【キーワード】Document Retrieval, Relevance Feedback, Support Vector Machines, Active Learning

14.

Y. Sinohara, A. Takasu (National Institute of Informatics), "Support Kernel Machine-Based Active Learning to Find Labels and a Proper Kernel Simultaneously," 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'07), Dec. 2007, U.K.

15.

T. Onoda, N. Ito, H. Yamasaki (Kyushu Electric Power Co., Inc.), "One-Class SVM Based Unusual Condition Monitoring for Risk Management of Hydroelectric Power Plants," International Joint Conference on Neural Networks 2007, Aug. 2007, U.S.A.

16.

T. Onoda, H. Murata, S. Yamada (National Institute of Informatics), "Support Vector Machines based Active Learning for the Relevance Feedback Document Retrieval," Web Intelligence '06 International Workshop on Intelligent Web Interaction, Dec., 2006, Hong Kong

17.

T. Onoda, S. Yamada (National Institute of Informatics), "Active Learning with Support Vector Machines in the Relevance Feedback Document Retrieval," Proceedings of International Conference on Control, Automation, Robotics and Vision 2006, Dec., 2006, Singapore
【キーワード】Document retrieval, Relevance feedback, Support vector machine, Active learning

18.

T. Onoda, N. Ito, H. Yamasaki (Kyushu Electric Power Co., Inc.), "Unusual Condition Mining for Risk Management of Hydroelectric Power Plants," ICDM-06 Workshops Workshop on Risk Mining 2006, Dec., 2006, Hong Kong

19.

T. Onoda, H. Murata, S. Yamada (National Institute of Informatics), "One Class Classification Methods based Non-Relevance Feedback Document Retrieval," Web Intelligence '06 International Workshop on Intelligent Web Interaction, Dec., 2006, Hong Kong

20.

F. Tsutsumi, "Interactive Machine Learning tool with Automatic Tagging for Video Recognition System," Proceedings of UIST'06 (The nineteenth annual ACM Symposium on User Interface Software and Technology), Oct. 2006, Switzerland

21.

T. Onoda, H. Murata, S. Yamada (National Institute of Informatics), "Non-Relevance Feedback Document Retrieval based on One Class SVM and SVDD," International Joint Conference on Neural Networks 2006, July 2006, Canada

22.

Y. Nakano, H. Murata, K. Yoshimoto, S. Hidaka (Tokyo University of Agriculture and Technology), M. Tadokoro (Tokyo University of Agriculture and Technology), K. Nagasaka (Tokyo University of Agriculture and Technology), "Non-Intrusive Electric Appliances Load Monitoring System - Performance Test Results at Real Households-," International Conference on Electrical Engineering 2006 (ICEE2006), July 2006, Korea
【キーワード】Non-Intrusive Monitoring, Household Electric Appliances, Harmonics, Support Vector Machine, Radial Basis Function Network, Load Survey, Performance Test

23.

Y. Nakano, H. Murata, K. Yoshimoto, S. Hidaka (Tokyo University of Agriculture and Technology), M. Tadokoro (Tokyo University of Agriculture and Technology), K. Nagasaka (Tokyo University of Agriculture and Technology), "Non-Intrusive Electric Appliances Load Monitoring System Using Harmonic Pattern Recognition - Performance Test Results at Real Households -," 4th International Conference on Energy Efficiency in Domestic Appliances and Lighting (EEDAL '06), June 2006, UK

24.

T. Onoda,H. Murata,S. Yamada (National Institute of Informatics), "Comparison of Retrieval Efficiency between One Class SVM based and SVDD based Non-Relevant Feedback Document Retrieval," The International Conference on Computational Intelligence, Robotics and Autonomous Systems 2005, Dec. 2005, Singapore

25.

T. Onoda,H. Murata,S. Yamada (National Institute of Informatics), "One Class Support Vector Machine based Non-Relevance Feedback Document Retrieval," Proceedings of International Joint Conference on Neural Networks 2005, Aug. 2005, Canada

26.

山名 美智子,村田 博士,小野田 崇,大橋 徹(中部電力),加藤 誠二(中部電力):「パターン識別手法を用いた錆画像による腕金再利用判定法の性能評価」,電気学会論文誌(C部門),125巻7号,平成17年7月
【キーワード】パターン識別,サポートベクターマシン,腕金,錆画像

27.

H. Murata,T. Onoda,S. Yamada(National Institute of Informatics), "Non-Relevance Feedback Document Retrieval," Artificial Intelligence and Applications 2005, Feb. 2005, Austria, Proceedings of the 23rd IASTED International Multi-Conference, pp. 84-89

28.

T. Onoda,H. Murata,S. Yamada(National Institute of Informatics), "Non-Relevance Feedback Document Retrieval," 2004 IEEE Conference on Cybernetic and Intelligent Systems, Dec. 2004, Proceedings of IEEE Conference on Cybernetic and Intelligent Systems 2004, Singapore, pp. 456-461

29.

T. Onoda, H. Murata, S. Yamada (National Institute of Informatics), "Relevance feedback Document Retrieval Using Support Vector Machines," International Symposium on Methodologies for Intelligent Systems Workshop Active Mining 2003, Oct. 2003
【キーワード】Relevance Feedback, Document Retrieval, Classification, Vector Space Model, Support Vector Machine

30.

村田 博士,小野田 崇,由本 勝久,中野 幸夫:「屋外からの家庭内電気機器消費電力推定における機械学習手法の性能評価」,電気学会論文誌C,123巻7号,平成15年7月
【キーワード】モニタリングシステムス,非侵入型,回帰,ニューラルネットワーク,サポートベクターマシン,RBF ネットワーク

31.

T. Onoda, H. Murata, S. Yamada (National Institute of Informatics), "Relevance Feedback with Active Learning for Document Retrieval," International Joint Conference on Neural Networks 2003, July 2003

32.

T. Onoda, H. Murata, S. Yamada (National Institute of Informatics), "Interactive Document Retrieval with Active Learning," International Workshop on Active Mining 2002 in ICDM2002, Dec. 2002, Maebashi
【キーワード】Document Retrieval, Active Learning, Support Vector Machine, Relevance Feedback

33.

H. Murata, T. Onoda, "ESTIMATION OF POWER CONSUMPTION FOR HOUSEHOLD ELECTRIC APPLIANCES," 9th International Conference on Neural Information Processing, Nov. 2002, Singapore
【キーワード】Load monitoring system, Regression, Multi-layered perceptrons, Support vector machine, RBF networks

34.

小野田 崇:「Boostingの過学習とその回避」,電子情報通信学会論文誌,J85-D-II巻第5号,平成14年5月
【キーワード】AdaBoost,過学習,正則化,margin,サポートベクターマシン

35.

T. Onoda, H. Murata, Gunnar Raetsch (GMD),Klaus R. Mueller (GMD), "Experimental Analysis of Support Vector Machines with Different Kernels based on Non-Intrusive Monitoring Date," International Joint Conference on Neural Networks 2002, May 2002, U.S.A.
【キーワード】Support Vector Machines, Kernels, Non-Intrusive Monitoring

36.

小野田 崇:「Large Margin Classifiers -Introduction to Large Margin Classifiers-」,人工知能学会誌,17巻1号,平成14年1月
【キーワード】サポートベクターマシン,AdaBoost,マージン

37.

小野田 崇,Gunnar Ratsch (GMD),Klaus R. Muller (GMD):「直観的な学習制御パラメータを有するArcingアルゴリズム」,人工知能学会誌,16巻5号,平成13年9月
【キーワード】Arcing, AdaBoost,マージン,分類,サポートベクターマシン

38.

H. Murata, T. Onoda, "Applying Kernel Based Subspace Classification to a Non-intrusive Monitoring for Household Electric Appliances," International Conference on Artificial Neural Networks, Aug. 2001, Austria
【キーワード】Kernel Method, Subspace Classification, Support Vector Machine, Monitoring

39.

小野田 崇:「特集 サポートベクターマシン:その仕組みと応用−分類手法の新展開−」,オペレーションズ・リサーチ,46巻5号,平成13年5月
【キーワード】サポートベクターマシン,分類問題,マージン,数理計画問題

40.

小野田 崇:「サポートベクターマシンの概要」,オペレーションズ・リサーチ,46巻5号,平成13年5月
【キーワード】サポートベクターマシン,分類問題,マージン,数理計画問題

41.

小野田 崇,中野 幸夫:「家庭用電気機器オン・オフ動作判定へのサポートベクターマシンの適用」,オペレーションズ・リサーチ,46巻5号,平成13年5月
【キーワード】サポートベクターマシン,分類問題,マージン,数理計画問題

42.

T. Onoda, G. Raetsch, K.-R Mueller (GMD), "Applying Support Vector Machine and Boosting to a Non-Intrusive Monitoring System for Household Electric Appliances with Inverters," NC'2000 Second International ICSC Symposium on NEURAL COMPUTATION, May 2000, Germany
【キーワード】Support Vector Machine, Boosting, Monitoring

43.

T. Onoda, G. Ratsch, B. Scholkopf, A. J. Smola, S. Mika, K. R. Muller (GMD), "Robust Ensemble Learning for Data Mining," The 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Apr. 2000, Japan
【キーワード】Ensemble Learning, Data Mining, Adaboost

44.

小野田 崇,G. Ratsch,K. R. Mueller (GMD):「2値分類問題におけるAdaBoostの漸近特性解析と改善」,人工知能学会誌, 15巻2号,平成12年3月
【キーワード】Ensemble Learning, AdaBoost, Margin Distribution, Classification, Support Vector Machine

45.

A. Futakata, "Self-Organization of Digital Documents based on Process-Oriented Relations," Hawaii International Conference on System Sciences 2000, Jan. 2000, Hawaii
【キーワード】自己組織化,文書管理,マルチエージェント,情報共有,知識管理

46.

T. Onoda, "An Improvement of AdaBoost to Avoid Overfitting," International Conference On Neural Information Processing 98, Ogura Japan, Dec. 1998
【キーワード】Ensemble Learning, Adaboost, Margin Distribution, Generalization, Support Vectors, RBF networks

47.

T. Onoda, G. Ratsch, K. R. Muller, "ν-AdaBoost," Neural Information Processing Systems 98 Workshop, Dec. 1998, Breckenridge Colorado, U.S.A.
【キーワード】Ensemble Learning, Adaboost, Classification, Margin Distribution, RBF Networks

48.

G. Ratsch, T. Onoda, K. R. Muller, "Regularizing AdaBoost," Neural Information Processing Systems 98, Dec. 1998, Denver, U.S.A.
【キーワード】Ensemble Learning, Adaboost, Classification, Margin Distribution, RBF Networks

49.

T. Onoda, G. Ratsch, K.-R. Muller, "An Asymptotic Analysis of AdaBoost in the Binary Classification Case," International Conference on Artificial Neural Networks 98, Skoevde Sweden, Sep. 1998
【キーワード】Ensemble Learning, Adaboost, Margin Distribution, Classification, RBF networks

50.

小野田 崇:「翌日最大電力需要予測における最適なニューラルネットワーク構成の決定法」,電気学会論文誌B,平成10年5月
【キーワード】電力システム,需要予測,負荷予測,ニューラルネットワーク,情報量基準

51.

小野田 崇:「情報量基準を用いたニューラルネットワークの最適な内部表現の獲得」,人工知能学会誌 第13巻第3号,平成10年5月
【キーワード】Neural Network, Information Criterion, Model Selection, Machine Learning, Principal Components Analysis

52.

T. Shimada, A. Futakata, "Automatic Link Generation and Repair Mechanism for Document Management," Proceedings of the 31st Annual Hawaii International Conference on System Science, Vol. II, Jan. 1998
【キーワード】Document Management, Distributed Management, Open Systems, Hypertext

53.

T. Onoda, Y. Shinohara, "Information Criterion for Acquisition of Optimal Internal Representation in Neural Networks," IEEE International Conference on Neural Information Processing 97, Nov. 1997
【キーワード】Neural Network, Information Criterion

54.

小野田崇:「階層型ニューラルネットワークの情報量基準」,人工知能学会誌,第11巻第4号,平成8年7月
【キーワード】階層型ニューラルネットワーク,情報量基準

55.

T. Onoda, "Experimental Analysis of Generalization Capability on Information Criteria," IEEE International Conference on Neural Network 96, Jun. 1996
【キーワード】Neural Network, Information Criteria.

56.

T. Onoda, "Neural Network Information Criterion for the Optimal Number of Hidden Units," International Conference on Neural Network 95, Nov. 1995
【キーワード】Neural Network, Information Criteria.

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