学術論文
134. Taichi Tomono, Satoshi Hara, Yusuke Nakai, Kazuma Takahara, Junko Iida, Takashi Washio, A Bayesian Approach for Component Estimation in Nucleic Acid Mixture Models, Frontiers in Analytical Science, Sec. Chemometrics, Vol.3 (2024), DIO: 10.3389/frans.2023.1301602.
133. Yohei Miyashita, Tatsuro Hitsumoto, Hiroki Fukuda, Jiyoong Kim, Shin Ito,Naoki Kimoto, Koko Asakura, Yutaka Yata, Masami Yabumoto, Takashi Washio, Masafumi Kitakaze, Metabolic Syndrome is Linked to the Incidence of Pancreatic Cancer, eClinicalMedicine, Vol.67 (2023) Article No.102353, DOI: 10.1016/j.eclinm.2023.102353.
132. Kaoru Murakami, Shimpei I. Kubota, Kumiko Tanaka, … , Takashi Washio, Takasuke Fukuhara, Takanori Teshima, Masateru Taniguchi and Masaaki Murakami, High-precision rapid testing of omicron SARS-CoV-2 variants in clinical samples using AI-nanopore, Lab on a Chip, Royal Society of Chemistry, Vol.22 (2023), DOI: 10.1039/D3LC00572K.
131. Yasuyuki Morita, Takashi Washio, Yuta Nakashima, Accelerator tuning method using Autoencoder and Bayesian Optimization, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol.1057 (2023) Article No.168730, DOI: 10.1016/j.nima.2023.168730.
130. Seihou Jinnai, Naoto Shimohara, Kazunori Ishikawa, Kento Hama, Yohei Iimuro, Takashi Washio, Yasuyuki Watanabe, Yutaka Ie, Green-light wavelength-selective organic solar cells for agrivoltaics: dependence of wavelength on photosynthetic rate, Faraday Discussions, the Royal Society of Chemistry, Vol.250 (2023), DOI:10.1039/D3FD00141E.
129. Masaru Kondo, H. D. P. Wathsala, Kazunori Ishikawa, Daisuke Yamashita, Takeshi Miyazaki, Yoji Ohno, Hiroaki Sasai, Takashi Washio, Shinobu Takizawa, Bayesian Optimization-assisted Screening to Identify Improved Reaction Conditions for Spiro-dithiolane Synthesis, Molecules, Vol.28, No.13 (2023) Article No.5180, DIO:10.3390/molecules28135180.
128. Yohei Miyashita, Tatsuro Hitsumoto, Hiroki Fukuda, Jiyoong Kim, Takashi Washio and Masafumi Kitakaze, Predicting Heart Failure Onset in the General Population using a Novel Data-mining Artificial Intelligence Method, Scientific Report, Vol.13 (2023) Article No.4352, DOI : 10.1038/s41598-023-31600-0.
127. Masaru Kondo, H.D.P. Wathsala, Mohamed S.H. Salem, Kazunori Ishikawa, Satoshi Hara, Takayuki Takaai, Takashi Washio, Hiroaki Sasai and Shinobu, Bayesian optimization-driven parallel-screening on multi-parameters of micromixer-type and organocatalytic conditions in the flowbiaryl synthesis, Vol.5 (2022) Article No.148, DOI : 10.1038/s42004-022-00764-7.
126. Kai Ming Ting, Takashi Washio, Jonathan Wells, Hang Zhang and Ye Zhu, Isolation Kernel Estimators, Knowledge and Information Systems, Vol.65 (2022) pp.759–787, DOI:10.1007/s10115-022-01765-7.
125. Yuki Naito, Masaru Kondo, Yuto Nakamura, Naoki Shida,Kazunori Ishikawa, Takashi Washio, Shinobu Takizawa and Mahito Atobe, Bayesian optimization with constraint on passed charge for multiparameter screening of electrochemical reductive carboxylation in a flow microreactor, Chemical Communications, Vol.58 (2022) pp.3893-3896.
124. Takashi Kojima, Takashi Washio, Satoshi Hara and Masataka Koishi, Search Strategy for Rare Microstructure to Optimize Material Properties of Filled Rubber using Machine Learning Based Simulation, Computational Materials Science, Vol.204 (2022) Article No.111207.
123. Mitsuko Hayashi-Nishino, Kota Aoki, Akihiro Kishimoto, Yuna Takeuchi, Aiko Fukushima, Kazushi Uchida, Tomio Echigo, Yasushi Yagi, Mika Hirose, Kenji Iwasaki, Eitaro Shin’ya, Takashi Washio, Chikara Furusawa and Kunihiko Nishino, Identification of bacterial drug-resistant cells by the convolutional neural network in transmission electron microscope images, Frontiers in Microbiology, Vol.13 (2022) Article No.839718.
122. Takashi Kojima, Takashi Washio, Satoshi Hara, Masataka Koishi and Naoya Amino, Analysis on Microstructure Property Linkages of Filled Rubber Using Machine Learning and Molecular Dynamics Simulations, Polymers, Vol.13, No.16 (2021) No.2683.
121. Kai Ming Ting, Takashi Washio, Bi-Cun Xu and Zhi-Hua Zhou, Isolation Distributional Kernel: A New Tool for Point & Group Anomaly Detection, IEEE Transactions on Knowledge and Data Engineering (2021) pp.1-1.
120. Makusu Tsutsui, Kazumichi Yokota, Akihide Arima, Takashi Washio, Yoshinobu Baba and Tomoji Kawai, Detecting single molecule deoxylibonucleic acid in a cell using a three-dimensionally integrated nanopore, Small Method, Vol.5, No.9 (2021) No.2100542.
119. Eisuke Sato, Mayu Fujii, Hiroki Tanaka, Koichi Mitsudo, Masaru Kondo, Shinobu Takizawa, Hiroaki Sasai, Takeshi Washio, Kazunori Ishikawa, Seiji Suga, Application of an Electrochemical Microflow Reactor for Cyanosilylation: Machine Learning-Assisted Exploration of Suitable Reaction Conditions for Semi-Large Scale Synthesis, Vol.86, No.22 (2021) pp.16035-16044.
118. Kai Ming Ting, Jonathan R. Wells and Takashi Washio, Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning, Data Mining and Knowledge Discovery, Vol.35 (2021) pp.2282-2312.
117. Tetsuichi Wazawa, Ryohei Noma, Shusaku Uto, Kazunori Sugiura, Takashi Washio and Takeharu Nagai, A photoswitchable fluorescent protein for hours-time-lapse and sub-second-resolved super-resolution imaging, Microscopy, Vol.70, No.4 (2021) pp.340-352.
116. Masaru Kondo, Akimasa Sugizaki, Md.Imrul Khalid, H.D.P. Wathsala, Kazunori Ishikawa, Satoshi Hara, Takayuki Takaai, Takashi Washio, Shinobu Takizawa and Hiroaki Sasai, Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: Machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation, Green Chemistry, Vol.23, No.16 (2021) pp.5825-5831.
115. Masateru Taniguchi, Shohei Minami, Chikako Ono, Rina Hamajima, Ayumi Morimura, Shigeto Hamaguchi, Yukihiro Akeda, Yuta Kanai, Takeshi Kobayashi, Wataru Kamitani, Yutaka Terada, Koichiro Suzuki, Nobuaki Hatori, Yoshiaki Yamagishi, Nobuei Washizu, Hiroyasu Takei, Osamu Sakamoto, Norihiko Naono, Kenji Tatematsu, Takashi Washio, Yoshiharu Matsuura and Kazunori Tomono, Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection, Nature Communications, Vol.2 (2021) No.3726.
114. Makusu Tsutsui, Takayuki Takaai, Kazumichi Yokota, Tomoji Kawai and Takashi Washio, Deep learning-enhanced nanopore sensing of single-nanoparticle translocation dynamics, Small Methods, Vol.5, No.7 (2021) No.2100191.
113. Makusu Tsutsui, Sou Ryuzaki, Kazumichi Yokota, Yuhui He, Takashi Washio, Kaoru Tamada and Tomoji Kawai, Field effect control of translocation dynamics in surround-gate nanopores, Communications Materials, Vol.2 (2021) No.29.
112. Rui Yatabe, Atsushi Shunori, Bartosz Wyszynski, Yosuke Hanai, Atsuo Nakao, Masaya Nakatani, Akio Oki, Hiroaki Oka, Takashi Washio and Kiyoshi Toko, Odor Sensor System using Chemosensitive Resistor Array and Machine Learning, IEEE Sensors Journal, Vol.21, No.2 (2021) pp.2077-2088.
111. Takeshi Yoshida, Takashi Washio, Takahito Ohshiro and Masateru Taniguchi, Classification from Positive and Unlabeled Data Based on Likelihood Invariance for Measurement, Intelligent Data Analysis, Vol.25, No.1 (2021) pp.57-79.
110. Akihide Arima, Makusu Tsutsui, Takashi Washio, Yoshinobu Baba, and Tomoji Kawai, Solid-State Nanopore Platform Integrated with Machine-Learning for Digital Diagnosis of Virus Infection, Analytical Chemistry, Vol.93 (2020) pp.215-227.
109. Takashi Kojima, Takashi Washio, Satoshi Hara and Masataka Koishi, Synthesis of computer simulation and machine learning for achieving the best material properties of filled rubber, Scientific Reports, Vol.10 (2020) No.18127.
108. Shota Hattori, Rintaro Sekido, Iat Wai Leong, Makusu Tsutsui, Akihide Arima, Masayoshi Tanaka, Kazumichi, Yokota, Takashi Washio, Tomoji Kawai, and Mina Okochi, Yokota, Takashi Washio, Tomoji Kawai, and Mina Okochi Machine learning-driven electronic identifications of single pathogenic bacteria, Scientific Reports, Vol.10 (2020) No.15525.
107. Akihide Arima, Makusu Tsutsui, Takeshi Yoshida, Kenji Tatematsu, Tomoko Yamazaki, Kazumichi Yokota, Shun’ichi Kuroda, Takeshi Washio, Yoshinobu Baba and Tomoji Kawai, Digital pathology platform for respiratory tract diagnosis via multiplex single-particle detections, ACS Sensors, Vol.5, No.11 (2020) pp.3398-3403.
106. Makusu Tsutsui, Kazumichi Yokota, Yuhui He, Takashi Washio and Tomoji Kawai,
Nano-corrugated nanochannels for in-situ tracking of single-nanoparticle translocation dynamics, ACS Sensors, Vol.5, No.8 (2020) pp.2530-2536.
105. Yuki Komoto, Takahito Ohshiro, Takeshi Yoshida, Etsuko Tarusawa, Takeshi Yagi, Takashi Washio and Masateru Taniguchi, Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap, Scientific Reports, Vol.10 (2020) No.11244.
104. Kazuhiro Shindo, Hiroki Fukuda, Tatsuro Hitsumoto, Yohei Miyashita, Jiyoong Kim, Shin Ito, Takashi Washio Masafumi Kitakaze, Artificial Intelligence Uncovered Clinical Factors for Cardiovascular Events in Myocardial Infarction Patients with Glucose Intolerance, Cardiovascular Drugs and Therapy, Vol.34, No.4 (2020) pp.535-545.
103. Kazuhiro Shindo, Hiroki Fukuda, Tatsuro Hitsumoto, Shin Ito, Jiyoong Kim, Takashi Washio and Masafumi, Plasma BNP Levels and Diuretics Use as Predictors of Cardiovascular Events in Patients with Myocardial Infarction and Impaired Glucose Tolerance, Cardiovascular Drugs and Therapy, Vol.34, No.1 (2020) pp.79-88.
102. Masaru Kondo, H.D.P. Wathsala, Makoto Sako, Yutaro Hanatani, Kazunori Ishikawa, Satoshi Hara, Takayuki Takaai, Takashi Washio, Shinobu Takizawa and Hiroaki Sasai, Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut-Currier and [3+2] annulation sequence, Chemical Communications, Vol.56, No.8 (2019) pp.1259-1262.
101. Gaku Imamura, Kota Shiba, Genki Yoshikawa and Takashi Washio, Free-hand gas identification based on transfer function ratios without gas flow control, Scientific Reports, Vol.9 (2019) No.9768.
100. Sunil Aryal, Kai Ming Ting, Takashi Washio and Gholamreza Haffari, A comparative study of data-dependent approaches without learning in measuring similarities of data objects, Data Mining and Knowledge Discovery, Vol.34 (2019) pp.124-162.
99. Masateru Taniguchi, Takahito Ohshiro, Yuki Komoto, Takayuki Takaai, Takeshi Yoshida and Takashi Washio, High-Precision Single-Molecule Identification Based on Single-Molecule Information within a Noisy Matrix, The Journal of Physical Chemistry C, Vol.123 (2019) pp.15867-15873.
98. 安並 一浩, 矢壷 修, 鷲尾 隆, 高田 望, 衛星画像と電力潮流を利用した太陽光発電出力推定手法, 電気学会論文誌C, Vol.140, No.2 (2019) pp.129-136.
97. Kai Ming Ting, Ye Zhu, Mark Carman, Yue Zhu, Takashi Washio and Zhi-Hua Zhou, Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhoodalgorithms, Machine Learning, Vol.108, No.2 (2019) pp.331-376.
96. Makusu Tsutsui, Kazumichi Yokota, Takeshi Yoshida, Chie Hotehama, Hiroe Kowada, Yuko Esaki, Masateru Taniguchi, Takashi Washio and Tomoji Kawai, Identifying Single Particles in Air Using a 3D-Integrated Solid-State Pore, ACS Sensors, Vol.4, No.3 (2019) pp.748-755.
95. 安並一浩, 矢壷 修, 鷲尾 隆, 太陽光発電出力のサンプル値と電力潮流の共分散を利用した太陽光発電出力推定手法, 電気学会論文誌C, Vol.139, No.2 (2019) pp.161-169.
94. Patrick Blobaum, Dominik Janzing, Takashi Washio, Shohei Shimizu and Bernhard Scholkopf, Analysis of cause-effect inference by comparing regression errors,Peer Journal Computer Science, Vol.5 (2019) No.e169.
93. Toshihiro Yoshizumi, Tatsuro Goda, Rui Yatabe, Akio Oki, Akira Matsumoto, Hiroaki Oka, Takashi Washio, Kiyoshi Tokob and Yuji Miyahara, Field-effect transistor array modified by a stationary phase to generate informative signal patterns for machine learning-assisted recognition of gas-phase chemicals, Vol.4, No.2 (2019) pp.386-389.
92. Akihide Arima, Ilva Hanun Harlisa, Takeshi Yoshida, Makusu Tsutsui, Masayoshi Tanaka, Kazumichi Yokota, Wataru Tonomura, Jiro Yasuda, Masateru Taniguchi, Takashi Washio, Mina Okochi and Tomoji Kawai, Identifying Single Viruses Using Biorecognition Solid-State Nanopores, Journal of the American Chemical Society, Vol.140 (2018) pp.16834-16841.
91. Akihide Arima, Makusu Tsutsui, Ilva Hanun Harlisa, Takeshi Yoshida, Masayoshi Tanaka, Kazumichi Yokota, Wataru Tonomura, Masateru Taniguchi, Mina Okochi, Selective detections of singleviruses using solid-state nanopores, Scientific Reports,
Vol.8 (2018) No.16305.
90. Gaku Imamura, Kota Shiba, Genki Yoshikawa and Takashi Washio, Analysis of nanomechanical sensing signals; physical parameter estimation for gas identification, AIP (American Institute of Physics) Advances, Vol.8 (2018) No. 075007.
89. Hiroki Fukuda, Kazuhiro Shindo, Mari Sakamoto, Tomomi Ide, Shintaro Kinugawa, Arata Fukushima, Hiroyuki Tsutsui, Shin Ito, Akira Ishii, Takashi Washio and Masafumi Kitakaze, Elucidation of the Strongest Predictors of Cardiovascular Events in Patients with Heart Failure, eBioMedicine, Vol.33 (2018) pp.185-195.
88. Mari Sakamoto, Hiroki Fukuda, Jiyoong Kim, Tomomi Ide, Shintaro Kinugawa, Arata Fukushima, Hiroyuki Tsutsui, Akira Ishii, Shin Ito, Hiroshi Asanuma, Masanori Asakura, Takashi Washio and Masafumi Kitakaze, The impact of creating mathematical formula to predict cardiovascular events in patients with heart failure, Scientific Reports, Vol.8 (2018) No.3986.
87. Tetsuichi Wazawa, Yoshiyuki Arai, Yoshinobu, Kawahara, Hiroki Takauchi, Takashi Washio and Takeharu Nagai, Highly biocompatible super-resolution fluorescence imaging using the fast photoswitching fluorescent protein Kohinoor and SPoD-ExPAN with Lp-regularized image reconstruction, Microscopy, Vol.67, No.2 (2018) pp.89-98.
86. Makusu Tsutsui, Masayoshi Tanaka, Takahiro Marui, Kazumichi Yokota, Takeshi Yoshida, Akihide Arima, Wataru Tonomura, Masateru Taniguchi, Takashi Washio, Mina Okochi and Tomoji Kawai, Analytical Chemistry, Vol.90 (2018) pp.1511-1515.
85. Bo Chen, Kai Ming Ting, Takashi Washio and Ye Zhu, Local contrast as an effective means to robust clustering against varying densities, Machine Learning, Vol.107, No.8-10 (2018) pp.1621-1645.
84. Makusu Tsutsui, Takeshi Yoshida, Kazumichi Yokota, Hirotoshi Yasaki, Takao Yasui, Akihide Arima, Wataru Tonomura, Kazuki Nagashima, Takeshi Yanagida, Noritada Kaji, Masateru Taniguchi, Takashi Washio, Yoshinobu Baba and Tomoji Kawai, Discriminating single-bacterial shape using low-aspect-ratio pores, Scientific Reports, Vol.7, No.1 (2017) No.17371.
83. 安並一浩，鷲尾 隆, 日射強度と電力潮流の共分散を利用した太陽光発電出力推定手法の適用可能性評価, 電気学会論文誌B, Vol.137, No.7 (2017) pp.488-498.
82. Patrick Blobaum, Takashi Washio and Shohei Shimizu, Error Asymmetry in Causal and Anticausal Regression, Behaviormetrika, Vol.44, No.2 (2017) pp.491-512. 81. Kai Ming Ting, Takashi Washio, Jonathan R. Wells and Sunil Aryal, Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors, Machine Learning, Vol.106, No.1 (2017) pp.55-91.
80. Hiroki Fukuda, Hideaki Suwa, Atsushi Nakano, Mari Sakamoto, Miki Imazu, Takuya Hasegawa, Hiroyuki Takahama, Makoto Amaki, Hideaki Kanzaki, Toshihisa Anzai, Naoki Mochizuki, Akira Ishii, Hiroshi Asanuma, Masanori Asakura, Takashi Washio and Masafumi Kitakaze, Non-linear Equation using Plasma Brain Natriuretic Peptide Levels to Predict Cardiovascular Outcomes in Patients with Heart Failure, Scientific Reports, Vol.6 (2016) No.37073.
79. Satoshi Hara, Takafumi Ono, Ryo Okamoto, Takashi Washio and Shigeki Takeuchi, Quantum-state anomaly detection for arbitrary errors using a machine-learning technique, Physical Review A, Vol.94 (2016) No.04234.
78. Keisuke Nagata, Yoshinobu Kawahara, Takashi Washio and Akira Unami, Toxicogenomic prediction with graph-based structured regularization on transcription factor network, Fundamental Toxicological Sciences, Vol.3, No.2 (2016) pp.39-46.
77. Marina Demeshko, Takashi Washio, Yoshinobu Kawahara and Yuriy Pepyolyshev, A Novel Continuous and Structural VAR Modeling Approach and Its Application to Reactor Noise Analysis, ACM Trans. on Intelligent Systems and Technology, Vol.7, No.2 (2016) pp. 24:1-24:22.
76. Makusu Tsutsui, Yuhui He, Kazumichi Yokota, Akihide Arima, Sadato Hongo, Masateru Taniguchi, Takashi Washio, and Tomoji Kawai, Particle Trajectory-Dependent Ionic Current Blockade in Low-Aspect-Ratio Pores, ACS Nano, Vol.10, No.1 (2015) pp.803-809.
75. 安並一浩, 鷲尾隆, 太陽光発電出力変動分析のための時空間減衰モデルを用いた相互相関関数推定手法, 電気学会誌論文誌B, Vol.135, No.10 (2015) pp.613-623.
74. Keisuke Nagata, Yoshinobu Kawahara, Takashi Washio and Akira Unami, Toxicogenomic prediction with group sparse regularization based on transcription factor network information, Fundamental Toxicological Sciences, Vol.2 No.4 (2015) pp.161-170.
73. Bo Chen, Kai Ming Ting, Takashi Washio and Gholamreza Haffari, Half-space mass: a maximally robust and efficient data depth method, Machine Learning, Vol.100 (2015) pp.677-699.
72. Masafumi Kitakaze, Masanori Asakura1, Atsushi Nakano, Seiji Takashima and Takashi Washio, Data Mining as a Powerful Tool for Creating Novel Drugs in Cardiovascular Medicine: the Importance of a “Back-and-Forth Loop” between Clinical Data and Basic Research, Cardiovascular Drug and Therapy, Vol.29, No.3 (2015) pp.309-315. 71. Marina Demeshko, Abdel, Dokhane, Takashi Washio, Hakim Ferroukhi , Yoshinobu Kawahara and Carlos Aguirre, Application of Continuous and Structural ARMA Modeling for Noise Analyses of a BWR Coupled Core and Plant Instability Event, Annals of Nuclear Energy, Vol.75 (2015) pp.645-657.
70. Keisuke Nagata, Takashi Washiob, Yoshinobu Kawaharab and Akira Unamia, Toxicity prediction from toxicogenomic data based on class association rule mining,
Toxicology Reports, Vol.1 (2014) pp.1133-1142.
69. 安並一浩，鷲尾 隆, 堺太陽光発電所の実測データに基づくPV分布の平滑化効果への影響分析, 電気学会論文誌B, Vol.134, No.10 (2014) pp.856-865.
68. Jonathan R. Wells, Kai Ming Ting and Takashi Washio, LiNearN: A new approach to nearest neighbour density estimator, Pattern Recognition, Vol.47 (2014) pp.2702-2720.
67. Satoshi Hara, Takafumi Ono, Ryo Okamoto, Takashi Washio and Shigeki Takeuchi, Anomaly Detection in Reconstructed Quantumn StatesUsing a Machine Learning Technique, Physical Review A, Vol.89 (2014) No.022104
66. Tatsuya Tashiro, Shohei Shimizu, Aapo Hyvarinen and Takashi Washio, ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders, Neural Computation, Vol.26 (2014) pp.57-83.
65. Yasuhiro Sogawaa, Tsuyoshi Uenob, Yoshinobu Kawahara and Takashi Washio, Active learning for noisy oracle via density power divergence, Neural Networks, Vol.46 (2013) pp.133-143.
64. Akemi Yoshida, Masanori Asakura, Hiroshi Asanuma, Akira Ishii, Takuya Hasegawa, Tetsuo Minamino, Seiji Takashima, Hideaki Kanzaki1, Takashi Washio and Masafumi Kitakaze, Derivation of a mathematical expression for predicting the time to cardiac events in patients with heart failure: a retrospective clinical study, Hypertension Research, Vol.36, No.5 (2013) pp.450-456.
63. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu and Sunil Aryal,
DEMass: a new density estimator for big data, Knowledge and Information Systems,Vol.35, No.3 (2013) pp.493-524.
62. 十河泰弘, 植野剛, 河原吉伸, 鷲尾隆, Density Power Divergenceを用いたロバスト能動回帰学習, 人工知能学会論文誌, Vol.28, No.1 (2013) pp.13-21.
61. Satoshi Hara and Takashi Washio, Learning a Common Substructure of Multiple Graphical Gaussian Models, Neural Networks, Vol.38 (2012) pp.23-38.
60. Hiroshi Kuwajima, Takashi Washio and Lim Ee-Peng, Fast and Accurate PSD Matrix Estimation by Row Reduction, IEICE TRANSACTIONS on Information and Systems, Vol. E95-D, No.11 (2012) pp.2599-2612.
59. Akihiro Inokuchi and Takashi Washio, FRISSMiner: Mining Frequent Graph Sequence Patterns Induced by Vertices, IEICE TRANSACTIONS on Information and Systems, Vol. E95-D, No.6 (2012) pp.1590-1602.
58. Satoshi Hara, Yoshinobu Kawahara, Takashi Washio, Paul von Bunau, Terumasa Tokunaga and Kiyohumi Yumoto, Separation of stationary and non-stationary sources with a generalized eigenvalue problem, Neural Networks, Vol.33 (2012) pp.7-20.
57. Yasuhiro Sogawa, Shohei Shimizu, Teppei Shimamura, Aapo Hyvarinen, Takashi Washio and Seiya Imoto, Estimating Exogenous Variables in Data with More Variables than Observations, Neural Networks, Vol.24, No.8 (2011) pp.875-880.
56. Yoshinobu Kawahara, Shohei Shimizu and Takashi Washio, Analyzing relationships among ARMA processes based on non-Gaussianity of external influences, Neurocomputing, Vol.74, No.12-13 (2011) pp.2212-2221.
55. Shohei Shimizu, Takanori Inazumi, Yasuhiro Sogawa, Aapo Hyvarinen, Yoshinobu Kawahara, Takashi Washio, Patrik O. Hoyer and Kenneth Bollen, DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model, Journal of Machine Learning Research, Vol.12 (2011) pp.1225-1248.
54. Viet Phuong Nguyen, Takashi Washio and Tomoyuki Higuchi、A new particle filter for high-dimensional state-space models based on intensive and extensive proposal distribution、International Journal of Knowledge,Vol.2, No.4 (2010) pp.284-311.
53. Katsutoshi Yada, Takashi Washio and Yasuharu Ukai, Modelling deposit outflow in financial crises: Application to branch management And customer relationship management, Int. J, Advanced Intelligence Paradigms, Vol.2, No.2/3 (2009) pp.254-270.
52. 城戸 健太郎，桑島 洋，鷲尾 隆, ユークリッド距離の高速高精度推定と範囲問い合わせへの応用, 情報処理学会論文誌，Vol.50, No.5 (2009) pp.1493-505.
51. Viet Phoung Nguyen and Takashi Washio, Modeling Dynamic Substate Chains among Massive Sates, Intelligent Data Analysis, Vol.12, No.3 (2008) pp.271-291.
50. Alexandre termier, Marie-Christine Rousset, Michele Sebag, Kouzou Ohara, Takashi Washio and Hiroshi Motoda, DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm, IEEE Transactions on Knowledge and Data Engineering, Vol.20, No.2 (2008) pp.300-320.
49. 鷲尾 隆，樋口知之，井元清哉，玉田嘉紀，佐藤健，元田浩, グラフマイニングとその統計的モデリングへの応用, 統計数理 Vol.54, No.2 (2007) pp.315-331.
48. Takashi Washio, Koutarou Nakanishi and Hiroshi Motoda, A Classification Method Based on Subspace Clustering and Association Rules, New Generation Computing, Vol.25 (2007) pp235-245.
47. Toshiko Wakaki, Hiroyuki Itakura, Masaki Tamura, Hiroshi Motoda and Takashi
Washio, A study on rough set-aided feature selection for automatic web-page classification, WIAS Journal, Vol.4, No.4 (2006) pp.431-441.
46. 中西 耕太郎，鷲尾 隆，光永 悠紀，藤本 敦，元田浩, 部分空間クラスタリングと相関規則に基づく分類学習手法, 人工知能学会論文誌 Vol.21, No.6 (2006) pp.526-536.
45. 光永 悠紀，鷲尾 隆，元田浩, 適応的密度基準に基づく部分空間クラスタリングを用いた定量的多頻度密度アイテム集合のマイニング, 人工知能学会論文誌 Vol.21, No.5 (2006) pp.439-449.
44. Fuminori Adachi, Takashi Washio and Hiroshi Motoda, Scientific Discovery of Dynamic Models Based on Scale-Type Constraints, IPSJ Transactions on Mathematical Modeling and Its Applications, Vol.47, No.SIG14 (TOM15) (2006) pp.31-42
43. Katsuyoshi Yada, Hiroshi Motoda, and Takashi Washio, Consumer Behavior Analysis by Graph Mining Technique, New Mathematics and Natural Computation, Vol.2 (2006) pp.59-68.
42. Fuminori Adachi, Takashi Washio, Atsushi Fujimoto and Hiroshi Motoda, Multi-structure Information Retrieval Method Based on Transformation Invariance, New Generation Computing, Vol. 23, No. 4 (2005) pp.291-314.
41. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, A General Framework for Mining Frequent Subgraphs from Labeled Graphs, Journal of Fundamenta Informatiae, Special issue on Advances in Mining Graphs, Trees and Sequence, Vol.66, No.1-2 (2005) pp.53-82.
40. Jiyoong Kim, Takashi Washio, Masakazu Yamagishi, Yoshio Yasumura, Satoshi Nakatani, Kazuhiko Hashimura, Akihisa Hanatani, Kazuo Komamura, Kunio Miyatake, Soichiro Kitamura, Hitonobu Tomoike and Masafumi Kitakaze, A novel data mining approach to the identification of effective drugs or combinations for targeted endpoints application to chronic heart failure as a new form of evidence-based medicine, Cardiovascular Drugs and Therapy, Vol.18, No. 6 (2004) pp.483-489.
39. Takashi Washio, Hiroshi Motoda and Yuji Niwa, Enhancing the Plausibility of Law Equation Discovery through Cross Check among Multiple Scale-type-based Models, Journal of Experimental & Theoretical Artificial Intelligence, Vol.17, No.1-2 (2005) pp.129-143.
38. Kenichi Yoshida, Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Teruaki Homma, Akihiro Hakashima, Hiromitsu Fujikawa and Katsuyuki Yamazaki, Density-Based Spam Detector, IEICE Trans. Inf. & Syst., Vol.E87-D, No.12 (2004) pp.2678-2688.
37. 猪口 明博, 鷲尾 隆, 元田 浩, 多頻度グラフマイニング手法の一般化, 人工知能学会論文誌, Vol. 19, No. 5 (2004) pp.368-378.
36. 吉田哲也, 和田卓也, 元田 浩, 鷲尾 隆, 記述長に基づく適応的Ripple Down Rules法, 人工知能学会論文誌, Vol.19, No.6 B (2004) pp.460-471.
35. Tetsuya Yoshida, Takuya Wada, Hiroshi Motoda and Takashi Washio, Adaptive Ripple Down Rules Method Based on Minimum Description Length Principle, Intelligent Data Analysis, Vol.8 (2004) pp.239-265.
34. 金 智隆, 磯村 正, 鷲尾 隆, 北風 政史, 医療情報に対する新しいデータや解析手法の適用, 日本エム・イー学会誌, 生体工学, Vol.41, Supp1.1 (2003) 第41巻特別号, S4-4, pp.35.
33. 鷲尾 隆, 金 智隆, 北風 政史, データマイニングとそのBiomedical Engineeringへの適用, 日本エム・イー学会誌, 生体工学, Vol.41, Supp1.1 (2003) 第41巻特別号, S4-1, pp.32.
32. 西村芳男, 鷲尾 隆, 吉田哲也, 元田 浩, 猪口明博, 岡田 孝, ＡＧＭアルゴリズムの高速化と立体構造解析への適用, 人工知能学会論文誌,Vol.18, No.5 C (2003) pp.257-268.
31. Takashi Washio and Hiroshi Motoda, State of the Art of Graph-Based Data Mining, ACM, SIGKDD Explorations, Vol.5, No.1 (2003) pp.59-68.
30. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, Complete Mining of Frequent Patterns from Graphs: Mining Graph Data, Machine Learning, Vol.50 (2003) pp.321-354.
29. Takashi Matsuda, Hiroshi Motoda and Takashi Washio, Graph-Based Induction and Its Applications, Advanced Engineering Informatics, Vol.16, No.2 (2003) pp.135-143.
28. Masahiro Terabe, Takashi Washio, Hiroshi Motoda, Osamu Katai and Tetsuo Sawaragi, Attribute Generation Based on Association Rules, Knowledge and Information Systems, Vol.4 (2002) pp.329-349.
27. 和田卓也, 元田 浩, 鷲尾 隆, 最小記述長原理を用いた帰納学習のRipple Down Rules法への統合化, 人工知能学会誌, Vol.16, No.2 (2001) pp.268-278.
26. 寺邊正大, 鷲尾 隆, 元田 浩, S3Baggingによる高速な分類生成, 情報処理学会論文誌:数理モデル化と応用, Vol.42, No.SIG14 (TOM5) (2001) pp.25-38.
25. Akihiro Inokuchi, Takashi Washio, Takashi Okada and Hiroshi Motoda, Applying the Apriori-Based Graph Mining Method to Mutagenesis Data Analysis, Journal of Computer Aided Chemistry, Vol.2 (2001) pp.87-92.
24. 堀 聡, 瀧 寛和, 鷲尾 隆, 元田 浩, データマイニングを用いた市場品質監視システム, 電気学会論文誌Ｃ, Vol.121-C, No.8 (2001) pp.1289-1295.
23. 松田 喬, 元田 浩, 鷲尾 隆, 一般グラフ構造データに対するGraph-Based Inductionとその応用, 人工知能学会論文誌, Vol.16, No.4 (2001) pp.363-374.
22. 鷲尾 隆, 元田 浩, 大規模システムに関する科学的連立方程式モデルの発見, 人工知能学会誌, Vol. 15, No. 6 (2000) pp.1107-1116.
21. 猪口明博, 鷲尾 隆, 元田 浩, 熊澤公平, 荒井尚英, 多頻度グラフパターンの完全な高速マイニング手法, 人工知能学会誌, Vol. 15, No. 6 (2000) pp.1052-1063.
20. 鷲尾 隆, 元田 浩, スケールタイプ制約に基づく科学的法則式の発見, 人工知能学会誌, Vol15, No.4 (2000) pp.681-692.
19. 鹿山俊洋, 堀内 匡, 元田 浩, 鷲尾 隆, 逐次ペア拡張による木構造データからの分類規則学習, 人工知能学会誌, Vol.15, No.3 (2000) pp485-494.
18. 寺邊正大, 片井 修, 椹木哲夫, 鷲尾 隆, 元田 浩, 相関ルールにもとづく属性生成手法, 人工知能学会誌, Vol.15, No.1 (2000) pp.187-197.
17. 和田卓也, 堀内 匡, 元田 浩, 鷲尾 隆, Ripple Down Rules法における知識獲得の特性評価に基づくデフォルト知識の決定規範, 人工知能学会誌, Vol.15, No.1 (2000) pp.177-186.
16. Yuji Niwa, Masahiro Terabe and Takashi Washio, Autonomous Recovery Execution in Nuclear Power Plant by the Agent, Cognition, Technology & Work, Vol.1 (1999) pp.197-210.
15. 鷲尾 隆, 元田 浩, 属性変量の尺度認知に基づく構成的法則発見手法, 認知科学, Vol.5, No.2 (1998) pp.80-94.
14. Takashi Washio and Hiroshi Motoda, Discovery of First-Principle Equations Based on Scale-Type-Based and Data-Driven Reasoning, Special Issue, KDD: Techniques & Applications, Knowledge-Based Systems, Vol.10, No.7 (1998) pp.403-411.
13. Takashi Washio, Masatake Sakuma and Masaharu Kitamura, A New Approach to Quantitative and Credible Diagnosis for Multiple Faults of Components and Sensors, Artificial Intelligence, Vol.91, No.1 (1997) pp.103-130.
12. 鷲尾 隆, 佐久間 正剛, 古川 宏, 北村 正晴, 原子力プラント知的診断における多様性評価基準, 日本原子力学会誌, Vol.37, No.12 (1995) pp.1128-1136.
11. 古川 宏, 口村 啓二, 鷲尾 隆, 北村 正晴, 原子力プラント知的診断のための情報多化, 日本原子力学会誌, Vol.37, No.8 (1995) pp.729-739.
10. 鷲尾 隆, 佐久間 正剛, 北村 正晴, 機器・センサ多重故障に関する定量的高信頼診断法人工知能学会誌, Vol.9, No.5 (1994) pp.719-729.
9. Takashi Washio and Masaharu Kitamura, Adaptive Microphone Array Technique for Remote Monitoring of Components in Nuclear Power Plants, Journal of Nuclear Science Technology, Vol.31, No.2 (1994) pp.91-101.
8. 鷲尾 隆, 北村 豊, 高橋 英明, ファジィ積分に基づくプラント内作業の人間信頼性解析, 日本原子力学会誌, Vol.33, No.10 (1991) pp.983-993.
7. 鷲尾 隆,物理法則に基づく外的駆動型因果性の導出, 人工知能学会誌, Vol.5, No.4 (1990) pp.482-491.
6. Masaharu Kitamura, Makoto Takahashi, Takashi Washio and Kazusuke Sugiyama, Synthesis of Heuristic Knowledge Base for Supporting Development of Goal-Oriented Reactor Noise Analysis Programs, Progress in Nuclear Energy, Vol.21 (1988) pp.213-221.
5. Takashi Washio, Masaharu. Kitamura and Kazusuke Sugiyama, Development of Failure Diagnosis Method Based on Transient Information of Nuclear Power Plant, Journal of Nuclear Science Technology, Vol.24, No.6 (1987) pp.452-461.
4. Takashi Washio, Masaharu Kitamura and Kazusuke Sugiyama, Qualitative Simulation of Power Plant Dynamics Based on Design knowledge, Control-Theory and Advanced Technology, Vol.2, No.3 (1986) pp.433-449.
3. Takashi Washio, Masaharu Kitamura, Kyuya Kotajima and Kazusuke Sugiyama, Automated Derivation of Failure Symptoms for Diagnosis of a Nuclear Power Plant, Annals Nuclear Energy, Vol.13, No.8 (1986) pp.459-465.
2. Masaharu Kitamura, Takashi Washio, Kyuya Kotajima and Kazusuke Sugiyama, Small-Sample Modeling Method for Nonstationary Reactor Noise Analysis, Annals Nuclear Energy, Vol.12, No.8 (1985) pp.399-407.
1. Masaharu Kitamura, Takashi Washio, Kyuya Kotajima and Kazusuke Sugiyama, Development of Methods for Analyzing Time-Varying Characteristics of Power Reactor Noise, Progress in Nuclear Energy, Vol.15 (1985) pp.57-65.
国際会議論文
221. Mohamed S. H. Salem, Masaru Kondo, H. D. P. Wathsala, Akimasa Sugizaki, Md. Imrul Khalid, Hiroaki Sasai, Takashi Washio, Shinobu Takizawa, Bayesian Optimization (BO)-driven Screening of Multiple Parameters: Towards Efficient Electrochemical and Flow Synthesis, The 15th International Kyoto Conference on New Aspects of Organic Chemistry (2023).
220. Takashi Washio, Measurement Informatics: Interdisciplinary innovation of measurement and information science, Keynote speech, PAKDD2023: The 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (2023).
219. Takashi Washio, Measurement Informatics – Key to innovate measurement technologies -, IEEE BigData 2022: 2022 IEEE International Conference on Big Data (2022) Tutorial 4.
218. Takashi Washio, Measurement Informatics and Its Application in Science, Proceedings of SciX2022: SciX (The Great SCIentific eXchange) Conference 2022 (2022) No.342.
217. Kai Ming Ting, Takashi Washio, Jonathan Wells and Hang Zhang, Isolation Kernel Density Estimation, Proceedings of IEEE ICDM 2021: 21st IEEE International Conference on Data Mining (2021) pp.619-628.
216. Yasuyuki Morita, Mitsuhiro Fukuda, Tetsuhiko Yorita, Hiroki Kanda, Kichiji Hatanaka, Takane Saitou, Hitoshi Tamura, Yusuke Yasuda, Takashi Washio, Yuta Nakashima, Masako Iwasaki, Hui Wen Koay, Keijiro Takeda, Takafumi Hara, Tsun Him Chong and Hang Zhao, Developments of control system for ion source using machine learning, Proceedings of International Conference on Ion Sources 2021 (ICIS21), Vol. 2224 (2021) pp.1-5.
215. Takeshi Yoshida and Eitaro Shin’ya, Class Prior Probability Estimation Using Density Ratio from Unlabeled and Contaminated Positive Datasets, Proceedings of PAKDD2021 Workshop on Machine Learning for MEasurement INformatics (MLMEIN) (2021) No.5.
214. Takayuki Takaai and Makusu Tsutsui, Unsupervised Noise Reduction for Nanochannel Measurement Using Noise2Noise Deep Learning, Proceedings of PAKDD2021 Workshop on Machine Learning for MEasurement INformatics (MLMEIN), Vol. LNAI12705 (2021) pp.44-56.
213. Kai Ming Ting, Takashi Washio, Bi-Cun Xu and Zhi-Hua Zhou, Isolation Distributional Kernel: A new tool for kernel based anomaly detection, Proceedings of SIG-KDD2020: Knowledge Discovery and Data Mining 2020 (2020) No.233.
212. Masaru Kondo, H.D.P. Wathsala, Makoto Sako, Yutaro Hanatani, Kazunori Ishikawa, Satoshi Hara, Takayuki Takaai, Takashi Washi, Shinobu Takizawa and Hiroaki Sasai, Efficient prediction of flow reaction conditions using machine-learning for enantioselective domino reaction, Proceedings of 13th International CeBiTec Symposium: Multi-Step Syntheses in Biology & Chemistry: An International Young Investigator (2019) No.1.
211. Satoshi Hara, Weichih Chen, Takashi Washio, Tetsuichi Wazawa and Takeharu Nagai, SPoD-Net: Fast Recovery of Microscopic Images Using Learned ISTA, Proceedings of The Eleventh Asian Conference on Machine Learning, Proceedings of Machine Learning Research (PMLR), Vol. PMLR101 (2019) pp.694-709. 210. Atsushi Shunori, Rui Yatabe, Bartosz Wyszynski, Yosuke Hanai, Atsuo Nakao, Masaya Nakatani, Akio Oki, Hiroaki Oka, Takashi Washio and Kiyoshi Toko, Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning, Proceedings of ISOEN 2019 – 18th International Symposium on Olfaction and Electronic Nose (2019) pp.1-3.
209. Yuka Yoneda, Mahito Sugiyama and Takashi Washio, Learning Graph Representation via Formal Concept Analysis, Proceedings of Thirty-second Conference on Neural Information Processing Systems (NIPS) 2018 Workshop (2018) pp.1-5.
208. Keiichi Kisamori, Takashi Washio, Yoshio Kameda and Ryohei Fujimaki, A Rare and Critical Condition Search Technique and its Application to Telescope Stray Light Analysis, Proceedings of SIAM International Conference on Data Mining 2018 (SDM18), (2018) No.567.
207. Patrick Bloebaum, Dominik Janzing, Takashi Washio, Shohei Shimizu and Bernhard Schoelkopf, Cause-Effect Inference by Comparing Regression Errors, Proceedings of AISTATS2018: The 21st International Conference on Artificial Intelligence and Statistics, (2018) No.298.
206. Takashi Washio, Gaku Imamura and Genki Yoshikawa, Measurement-oriented Machine Learning for Advanced Sensing, Proceedings of The MANA International Symposium 2018 (2018) No.1.
205. Takashi Washio, Measurement Oriented Machine Learning for Advanced Sensing Technologies, Proceedings of 4th Asia-Pacific World Congress on Computing Science 2017 (APWC on CSE 2017) (2017) No.1.
204. Takashi Washio, Gaku Imamura and Genki Yoshikawa, Machine Learning Independent of Population Distributions for Measurement, Proceedings of DSAA2017: 4th IEEE International Conference on Data Science and Advanced Analytics (2017) pp.212-221.
203. Patrick Bloebaum, Takashi Washio and Shohei Shimizu, A Novel Principle for Causal Inference in Data with Small Error Variance, Proceedings of European Symposium on Artificial Neural Networks (2017) pp.347-352.
202. Takashi Washio, Potential Social Impact of Compact and Smart Sensors in IoT Era, Proceedings of HICCS: The 50th Hawaii International Conference on System Sciences (2017) No.1.
201. Takashi Washio, Comparative Research on Social Risk Reduction by Smart Hazard Monitoring Sensors, Proceedings of HICCS: The 50th Hawaii International Conference on System Sciences (2017) No.1.
200. Shigeki Takeuchi and Takashi Washio, Quantum state estimation and discrimination, Proceedings of SPIE Photonics West OPTO: Advances in Photonics of Quantum Computing, Memory, and Communication X, Vol.157181 (2017) pp.1-2.
199. Yoshito Baba, Mahito Sugiyama and Takashi Washio, Finding Combinations of Binary Variables with Guaranteed Accuracy, Proceedings of NIPS 2016 Workshop on Adaptive and Scalable Nonparametric Methods in Machine Learning (2016) pp.5.
198. Takashi Washio, Defying the Gravity of Learning Curves: Are More Samples Better for Nearest Neighbor Anomaly Detectors?, Proceedings of SISAP 2016: 9th International Conference on Similarity Search and Applications (2016) No.1.
197. Takashi Washio, NanoScale and Ultratrace Sensing for IoT using Machine Learning and Ultratrace Sensing for IoT using Machine Learning, Proceedings of KES2016: 20th Annual Conference on Knowledge Based and Intelligent Information & Engineering Systems (2016) No.1.
196. Patrick Blobaum, Shohei Shimizu and Takashi Washio, Error Asymmetry in Causal and Anticausal Regression, Working Notes of Workshop on Statistical Causal Inference and its Applications to Genetics (CRM) (2016) No.1.
195. Takeshi Yoshida, Takashi Washio, Akira Ishii, Tomoji Kawai, Masateru Taniguchi, Makusu Tsutsui and Kazumichi Yokota, Identification of Microorganisms Using Machine Learning Based on Nanopore Sensing Output, Proceedings of ImPACT International Symposium on InSECT 2016 (2016) No.1.
194. Takashi Washio,Accurate Sensing Based on Output Integration of Multiple Devices Using Machine Learning, Proceedings of ImPACT International Symposium on InSECT 2016 (2016) pp.15.
193. Sunil Aryal, Kai Ming Ting, Gholamreza Haffari and Takashi Washio, Beyond tf-idf and cosine distance in documents dissimilarity measure, Proceedings of the 11th Asia Information Retrieval Societies Conference (AIRS 2015), Vol. LNCS9460 (2015) pp.400-406.
192. Kazuhiro Yasunami and Takashi Washio, Applicability of a PV Power Output Estimation Method using Low Sampling Rates, Proceedings of International Workshop on Time Series Data Analysis and its Applications (TSDAA 2015) (2015) No.III-2.
191. Patrick Blobaum, Shohei Shimizu and Takashi Washio, Discriminative and Generative Models in Causal and Anticausal Settings, Proceedings of the Second Workshop on Advanced Methodologies for Bayesian Networks (AMBN 2015), Vol. LNAI9505 (2015) pp.209-221.
190. Kazuhiro Yasunami and Takashi Washio, An Accuracy Evaluation of PV Power Output Estimation Method Using Covariance between Solar Radiation Intensity and Power Flow, Proceedings of IEEE Power and Energy Society ISGT (Innovative Smart Grid Technology) (2015) No.215.
189. Keisuke Nagata, Takashi Washio, Yoshinobu Kawahara and Akira Unami, New toxicogenomic predictive model for decreased reticulocytes based on gene expressions in liver of rats built with class association rule mining, Proceedings of ISMB/ECCB 2015: 23rd Annual International Conference on Intelligent Systems for Molecular Biology/ 14th European Conference on Computational Biology (2015) No.1. 188. Kazuhiro Yasunami and Takashi Washio, An Estimation Method of PV Power Output in Electric Power Systems by using Covariance between Solar Radiation Intensity and Power Flow, Proceedings of International Conference on Electrical Engineering (ICEE) 2015 (2015) No.ICEE15A-040.
187. Sunil Aryal, Kai Ming Ting, Gholamreza Haffari and Takashi Washio, mp-dissimilarity: A data dependent dissimilarity measure, Proceedings of ICDM2014: IEEE International Conference on Data Mining (2014) No.DM570.
186. Sunil Aryal, Kai Ming Ting, Jonatha,n Wells and Takashi Washio, Improving iForest with relative mass, Proceedings of PAKDD2014: The 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Vol. LNCS 8444 (2014) pp.510-521. 185. Patrick Blobaum, Shohei Shimizu and Takashi Washio, A performance comparison of generative and discriminative models in causal and anticausal problems, Proceedings of Seventeenth International Conference on Artificial Intelligence and Statistics (2014) No.L008.
184．Marina Demeshko, Takashi Washio and Yoshinobu Kawahara, A Novel Structural AR Modeling Approach for a Continuous Time Linear ,gs: Risk Management for Complex Socio-Technical Systems, Vol.TANSAO109 (2013) pp.2330.
182. Takashi Washio and Yukito Iba, Rare Flood Scenario Analysis Using Observed Rain Fall Data, Proceedings of JSST 2013: International Conference on Simulation Technology (2013) No.1.
181. Takashi Washio, Issues for Modeling from Big Data, Working Notes of Workshop on Computation: Theory and Practice (2013) No.1.
180．Kento Kadowaki, Shohei Shimizu and Takashi Washio, Estimation of Causal Structures in Longtudinal Data Using Non-Gaussianit, Proceedings of 2013 IEEE International Workshop on Machine Learning for Signal Processing (2013) No.13.
179. Christiane Kamdem Kengne, Leon Constantin Fopa, Alexandre Termier, Noha Ibrahim, Marie-Christine Rousset, Takashi Washio and Miguel Santana, Efficiently Rewriting Large Multimedia Application Execution Traces with few Event Sequences,Proceedings of The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIG-KDD2013) (2013) pp.1348-1356.
178. Naoki Tanaka, Shouhei Shimizu and Takashi Washio, Estimation of causal direction in the presence of latent confounders using a Bayesian LiNGAM mixture model, Working Notes of Workshop on Causality: Perspectives from different disciplines (2012) No.1.
177. Christiane Kamdem Kengne, Leon Constantin Fopa, Noha Ibrahim, Alexandre Termier, Marie-Christine Rousset and Takashi Washio, Enhancing the Analysis of Large Multimedia Applications Execution Traces with FrameMiner, Proceedings of PTDM: Workshop on Practical Theories of Data Mining, ICDM 2012: The IEEE International Conference on Data Mining (2012) pp.595-602.
176. Satoshi Hara and Takashi Washio, Anomalous Neighborhood Selection, Proceedings of OEDM: Workshop on Optimization Based Techniques for Emerging Data Mining, ICDM 2012: The IEEE International Conference on Data Mining (2012) pp.474-480.
175. Kittitat Thamvitayakul, Shohei Shimizu, Tsuyoshi Ueno, Takashi Washio and Tatsuya Tashiro, Bootstrap confidence intervals in DirectLiNGAM, Proceedings of RIKD: Workshop on Reliability Issues in Knowledge Discovery, ICDM 2012: The IEEE International Conference on Data Mining (2012) pp.660-668.
174. Tsuyoshi Ueno, Yoshinobu Kawahara, Takashi Washio and Kohei Hayashi, Weighted likelihood Policy search with model selection, Proceedings of Neural Information Processing Systems 2012, Vol.25 (2012) No. W89.
173. Yasuhiro Sogawa, Tsuyoshi Ueno, Yoshinobu Kawahara and Takashi Washio, Robust Active Learning for Linear Regression via Density Power Divergence, Proceedings of the 19th International Conference on Neural Information Processing (ICONIP2012), Vol.LNCS7665 (2012) pp.594-602.
172. Satoshi Hara and Takashi Washio, Group Sparse Inverse Covariance Selection with a Dual Augmented Lagrangian Method, Proceedings of the 19th International Conference on Neural Information Processing (ICONIP2012), Vol.LNCS7665 (2012) pp.108 -115.
171. Marina Demeshko and Takashi Washio, A Novel Structural ARMA Modeling Approach to Reactor Noise Analysis, Proceedings of REACTOR NOISE Knowledge Transfer Meeting 2012 (RNKTM2012) (2012) No.5.
170. Tatsuya Tashiro, Shohei Shimizu, Aapo Hyvarinen and Takashi Washio, Estimation of Causal Orders in a Linear Non-Gaussian Acyclic Model: A Method Robust against Latent Confounders, Proceedings of Artificial Neural Networks and Machine Learning (ICANN2012), Vol. LNCS7553 (2012) pp.491 -498.
169. Kai Ming Ting, Takashi Washio, Jonathan Wells and Tony Liu, Density Estimation based on Mass, Proceedings of ICDM2011: The IEEE International Conference on Data Mining series (2011) pp.715 -724.
168. Shinya Miyazaki, Takashi Washio and Katsutoshi Yada, Analysis of Residence Time in Shopping using RFID Data -An Application of the Kernel density estimation to RFID, Working Notes of DMS2011: Workshop on Data Minig For Service: The IEEE International Conference on Data Mining series (ICDM2011) (2011) pp.1170 -1176.
167. Yoshinobu Kawahara and Takashi Washio, Prismatic Algorithm for Discrete D.C. Programming Problem, Proceedings of NIPS2011: Twenty-Fifth Annual Conference on Neural Information Processing Systems, Vol. 24 (2011) pp.2106 -2114.
166. Takashi Washio, A New Approach to Bayesian Estimation over the Curse of Dimensionality, Working Notes of Workshop on Machine Learning and Intelligent Autonomous Systems, AI-2011 Thirty-first SGAI International Conference on Artificial (2011) No.1.
165. Satoshi Hara and Takashi Washio, Common Substructure Learning of Multiple Graphical Gaussian Models, Proceedings of ECML-PKDD2011: European Conference on Machine Learning and Principle and Practice of Knowledge Discovery in Databases 2011, Vol. LNCS6912 (2011) pp.1 -16.
164. Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto and Yoshinobu Kawahara, Discovering Causal Structures in Binary Exclusive-or Skew Acyclic Models, Proceedings of UAI2011: The 27th Conference on Uncertainty in Artificial Intelligence (2011) pp.373 -382.
163. Kohei Ichikawa, Edward Ip, Katsuyoshi Yada and Takashi Washio, Application of DNA Sequence Alignment Algorithm to Classification of Shopping Paths through a Supermarket, Working Notes of Workshop on Data Mining Marketing, SIAM: SIAM Conference on Data Mining (SDM11) (2011) No.2
162. Satoshi Hara, Yoshinobu Kawahara, Takashi Washio and Paul von Bunau, Stationary Subspace Analysis as a Generalized Eigenvalue Problem, Neural Information Processing, Theory and Algorithms Lecture Notes in Computer Science, Vol.LNCS6443 (2010) pp.422 -429.
161. Takanori Inazumi, Shohei Shimizu and Takashi Washio, Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models, Proceedings of Ninth International Conference on Latent Variable Analysis and Signal Separation, Vol. LNCS6365 (2010) pp.221 -228.
160. Yasuhiro Sogawa, Shohei Shimizu, Aapo Hyvarinen, Takashi Washio, Teppei Shimamura and Seiya Imoto, Discovery of Exogenous Variables in Data with More Variables than Observations, Proceedings of 20th International Conference on Artificial Neural Networks (ICANN2010) (2010) pp.67-76.
159. Kohei Ichikawa, Katsutoshi Yada and Takashi Washio, A Classification Method Using DNA Sequence Alignment Algorithms for Path Data in Supermarket,Proceedings of 34th Annual Conference of the German Classification Society (GfKl) (2010) pp.105.
158. Keiji Takai, Takashi Washio, Katsutoshi Yada and Rajeev Kohli, Estimation of Exposure Time and Purchase Probability for Supermarket Categories from RFID data,Proceedings of 34th Annual Conference of the German Classification Society (GfKl) (2010) pp.176.
157. Yasuhiro Sogawa, Shohei Shimizu, Yoshinobu Kawahara and Takashi Washio, An experimental comparison of linear non-Gaussian causal discovery methods and their variants, Proceedings of WCCI 2010 IEEE World Congress on Computational Intelligence, Joint Conference on Neural Networks (IJCNN), Vol. CFP10US-DVD (2010) pp.768-775.
156. Akihiro Inokuchi and Takashi Washio, GTRACE2: Improving Performance Using Labeled Union Graphs, Proceedings of PAKDD2010: The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Vol.LNAI6119 (2010) pp.178-188.
155. Akihiro Inokuchi and Takashi Washio, Mining Frequent Graph Sequence Patterns Induced by Vertices, Proceedings of SIAM Data Mining Conference (SDM) 2010, CP11 Graph Mining (2010).
154. Kohei Ichikawa, Katsutoshi Yada, Namiko Nakachi and Takashi Washio, Optimization of Budget Allocation for TV Advertising, Proceedings of KES2009: 13th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, J.D. Velasquez et al. (Eds.) Part II, LNAI 5712 (2009) pp.270-277.
153. Katsutoshi Yada, Takashi Washio and Yasuharu Ukai, Modeling Deposit Outflow in Financial Crises: Application to Brach Management and Customer Relationship Management, Proceedings of 2009: Far East and South Asia Meeting of the Econometric Society (2009) pp.63.
152. Shohei Shimizu, Aapo Hyvarinen, Yoshinobu Kawahara and Takashi Washio, Identification of an Exogenous Variable in a Linear non-Gaussian Structural Equation Model, The International Workshop on Data Mining and Statistical Science (DMSS2009) (2009) pp.78-86.
151. Shohei Shimizu, Aapo Hyvarinen, Yoshinobu Kawahara and Takashi Washio, A direct method for estimating a casual ordering in a linear non-Gaussian acyclic model, Proceedings of UAI2009: The 25th Conference on Uncertainty in Artificial Intelligence, Causality II & Graphical Models (2009) pp.506-513.
150. Akihiro Inokuchi and Takashi Washio, A Fast method to Mine Frequent Subsequences from Graph Sequence Data, Proceedings of ICDM2008: 2008 8th IEEE International Conference on Data Mining (2008) pp.303-312.
149. Kouzo Ohara and Takashi Washio, Isomorphism Identification by Using Graph Spectra and Its Application to Graph Mining, Proceedings of IASC2008: the Joint Meeting of 4th World Conference of the IASC and 6th Conference of the Asian Regional Section of the IASC on Computational Statistics & Data Analysis, (Invited) (2008) pp.229.
148. Takashi Washio, Katsutoshi Yada, Yasuharu Ukai and Hisao Nagaoka, Modeling Bank Runs by Data Mining to Manage Financial Crises, Proceedings of International Conference of Socionetwork Strategies and Policy Grid Computing, Social Agent modeling and Computation for Policy Making 2008, (Invited, Keynote Speech) (2008) pp.11-13.
147. Kouzou Ohara, Takashi Washio and Duy Vinh Nguyen, On Feasibility of Graph Spectrum-based Frequent Sub-graph Mining, Proceedings of 3rd International Workshop on Data Mining and Statistical Science (DMSS2008) (2008) pp.9-11.
146. Akihiro Inokuchi and Takashi Washio, Feasibility of Graph Sequence Mining based on Admissibility Constraints, Proceedings of 3rd International Workshop on Data Mining and Statistical Science (DMSS2008) (2008) pp.1-4.
145. Katsutoshi Yada, Takashi Washio, Yasuharu Ukai and Hisao Nagaoka, A Bank Run Model in Financial Crises, Proceedings of KES 2008 (12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems) Part II, LNAI 5178 (2008) pp.703-710.
144. Kentarou Kido, Hiroshi Kuwajima and Takashi Washio, A Range Query Approach for High Dimensional Euclidean Space Based on EDM Estimation, Proceedings of the 8th SIAM International Conference on Data Mining (SDM2008), Edited by Mohammed J. Zaki, Ke Wang, Chid Apte and Haesun Park (2008) pp.387-398.
143. Hiroshi Kuwajima and Takashi Washio, Large PSD Matrix Estimation from Partial Elements, Workingnotes 7th IEEE International Conference on Data Mining – Workshop on High Performance Computing: 0-7695-3019-2/07 2007 IEE DOI 10.1109/ICDMW.2007.24 (2007) pp.337-342.
142. Hiroshi Kuwajima and Takashi Washio, Fast PSD Matrix Estimation by Column Reductions, ISM Report on Research and Education No.25, The International Workshop on Data-Mining and Statistical Science (DMSS2007) (2007) pp.179-189.
141. Alexandre Termier, Yoshinori Tamada, Kazuyuki Numata, Seiya Imoto, Takashi Washio and Tomoyuki Higuchi, DIGDAG, a first algorithm to mine closed frequent embedded sub-DAGs, Proceedings of MLG Workshop 2007, Mining and Learning with Graphs (2007) pp.41-46.
140. Warodom Geamsakul, Takashi Matsuda, Tetsuya Yoshida, Kouzou Ohara, Hiroshi Motoda, Takashi Washio Hideto Yokoi and Katsuhiko Takabayashi, Analysis of Hepatitis Dataset by Decision Tree Based on Graph-Based Induction, New Frontiers in Artificial Intelligence, JSAI 2003 and JSAI 2004 Conference and Workshop, Springer LNAI 3609 (2007) pp.5-28.
139. Takashi Washio, Yasuo Shinnou, Katsutoshi Yada, Hiroshi Motoda and Takashi Okada, Analysis on a Relation Between Enterprise Profit and Financial State by Using Data Mining Techniques, New Frontiers in Artificial Intelligence, JSAI 2006 Conference and Workshop, (Tokyo, Japan, 2006) Revise Selected Papers, LNAI 4384, Springer (2007) pp.305-316.
138. Kiyoto Takabayashi, Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda and Takashi Washio, Extracting Discriminative Patterns from Graph Structured Data using constrained Searches, Proceedings of the 2006 Pacific Rim Knowledge Acquisition Workshop (PKAW 2006), Workshop held in conjunction with the 9th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2006) (2006) pp.62-72.
137. Kenta Fukata Takashi Washio and Hiroshi Motoda, A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis, Proceedings of 6th IEEE International Conference on Data Mining, Workshop on Risk Mining 2006 (2006) #27020114.
136. Nguyen Viet Phuong and Takashi Washio, Modeling Dynamics Substate Chain among Massive States for Prediction, Proceedings of 6th IEEE International Conference on Data Mining, Workshop on Risk Mining 2006 (2006) #27020094.
135. Nguyen Viet Phuong and Takashi Washio, Modeling Dynamics of Massive Dimensional and Complex Systems, Proceedings of DMSS2006: The International Workshop on Data Mining and Statistical Science (2006) pp.125-132.
134. Nguyen Viet Phuong and Takashi Washio, High-Order Substate Chain Prediction Based on Massive Sensor Outputs, Proceedings of the 4th International Workshop on Knowledge Discovery from Data Streams, 17th European Conference on Machine Learning (ECML) and 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) (2006) pp.13-22.
133. Kiyoto Takabayashi, Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda and Takashi Washio, Mining Discriminative Patterns from Graph Structured Data with Constrained Search, Proceedings of the Workshop on Mining and Learning with Graphs, 17th European Conference on Machine Learning (ECML) and 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) (2006) pp.205-212.
132. Takashi Washio, Koutarou Nakanishi, Hiroshi Motoda and Takashi Okada, Mutagenicity Risk Analysis by Using Class Association Rules, 2nd JSAI International Workshop, Post Proceedings of First International Workshop on Risk Management Systems with Intelligent Data Analysis (RMDA-2005),LNAI 4012, Washio, T.; Sakurai, A.; Nakajima, K.; Takeda H.; Tojo, S.; Yokoo, M.(Eds.) (2006) pp.436-445.
131. Takashi Washio, Yasuo Shinnou, Katsutoshi Yada, Hiroshi Motoda and Takashi Okada, Analysis on a Relation between Enterprise Profit and Financial Sate by Using Data Mining Techniques, Working Notes of RM2006: Workshop on Risk Mining, Data Mining for Detection, Analysis and Utilization of Risk Information, Collocated with the 20th National Meeting of JSAI 2006 (2006) pp.35-46.
130. Takashi Washio, Koutarou Nakanishi, Hiroshi Motoda and Takashi Okada, Mutagenicity Risk Analysis by Using Class Association Rules, Proceedings of JSAI 2005 Workshops, LNAI 4012 (Springer-Verlag 2006) pp.436-445.
129. Phu Chien Nguyen, Kouzou Ohara, Akira Mogi, Hiroshi Motoda and Takashi Washio, Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction, Proceedings of 10th Pacific-Asia Conference, Advances in Knowledge Discovery and Data Mining (PAKDD2006), LNAI 3918 (Springer, Heidelberg, Germany, 2006) pp.390-399.
128. Fuminori Adachi, Takashi Washio, Atsushi Fujimoto and Hiroshi Motoda, Development of Generic Search Method Based on Transformation Invariance, New Generation Computing, Vol. 23, No.4 (2005) pp.291-314
127. Takashi Washio, Yuki Mitsunaga and Hiroshi Motoda, Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering, Proceedings of the 5th IEEE International Conference on Data Mining (ICDM’05) (IEEE, New York, USA, 2005) pp.793-796.
126. Alexandre Termier, Marie-Christine Rousset, Michele Sebag, Kouzou Ohara, Takashi Washio and Hiroshi Motoda, Efficient Mining of High Branching Factor Attribute Trees, Proceedings of the 5th IEEE International Conference on Data Mining (ICDM’05) (IEEE, New York, USA, 2005) pp.785-788.
125. Takashi Washio, Fuminori Adachi and Hiroshi Motoda, SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos, Proceedings of 8th International Conference on Discovery Science (DS2005) (Springer, Heidelberg, Germany, 2005) pp.253-266.
124. Alexandre Termier, Marie-Christine Rousset, Michele Sebag, Kouzou Ohara, Takashi Washio and Hiroshi Motoda, Computation-Time Efficient and Robust Attribute Tree Mining with DRYADEPARENT, Proceedings of the 3rd International Workshop on Mining Graphs, Trees and Sequences (MGTS2005): ECML/PKDD 2005 (ECML/PKDD, Porto, Portugal, 2005) pp.63-76.
123. Takashi Washio, Koutarou Nakanishi and Hiroshi Motoda, Deriving Class Association Rules Based on Levelwise Subspace Clustering, Proceedings of 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2005), LNAI3721 (Springer, Heidelberg, Germany, 2005) pp.692-700.
122. Takashi Washio, Fuminori Adachi and Hiroshi Motoda, Discovering Time Differential Law Equations Containing Hidden State Variables and Chaotic Dynamics, Proceedings of 19th International Joint Conference on Artificial Intelligence (Professional Book Center, Denver, USA, 2005) pp.1642-1644.
121. Katsutoshi Yada, Hiroshi Motoda and Takashi Washio, A Data Mining for Graph Structure Data Helps to Discover New Knowledge in Consumer Behavior and Makes Profits, Proceedings CD of AMS International Retailing Conference (AMSIRC, Reims, France) pp.1-17.
120. Takashi Washio, Koutarou Nakanishi, Hiroshi Motoda and Takashi Okada, Mutagenicity Risk Analysis by Using Class Association Rules, Proceedings of International Workshop on Risk Management Systems with Intelligent Data Analysis (RMDA-2005): the 19th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI-2005) (JSAI, Tokyo, 2005) pp.23-34.
119. Warodom Geamsakul, Tetsuya Yoshida, Kouzou Ohara, Hiroshi Motoda, Takashi Washio, Hideto Yokoi and Katsuhiko Takabayashi, Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Inducction, Proceedings of Active Mining: Second International Workshop: Revised Selected Paper,Lecture Notes in Computer Science, Publisher: Springer-Verlag GmbH,ISSN: 0302-9743, Vol. 3430 (2005) pp.126-136.
118. Katsutoshi Yada, Yukinobu Hamuro, Naoki Katoh, Takashi Washio, Issey Fusamoto, Daisuke Fujishima and Takaya Ikeda, Data Mining Oriented CRM Systems Based on MUSASHI: C-MUSASHI, Proceedings of Active Mining: Second International Workshop: Revised Selected Paper, Lecture Notes in Computer Science, Publisher: Springer-Verlag GmbH ISSN: 0302-9743, Vol.3430 (2005) pp.152-162.
117. Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda and Takashi Washio, Cl-GBI: A Novel Approach for Extracting Typical Patterns from Graph-Structured Data, Proceedings of 9th Pacific-Asia Conference (PAKDD2005), LNCS3518 (Springer, Heidelberg, Germany, 2005) pp.639-649.
116. Kenichi Yoshida, Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Teruaki Homma, Akihiro Hakashima, Hiromitsu Fujikawa and Katsuyuki Yamazaki, Memory Management of Density-Based Spam Filter, Proceedings of 2005 Symposium on Applications and the Internet (Saint 2005) (Saint, Trento, Italy, 2005) pp.370-376.
115. Takashi Washio, Atsushi Fujimoto and Hiroshi Motoda, A Framework of Numerical Basket Analysis, Proceedings of 2005 Symposium on Applications and the Internet (Saint 2005) Workshops (Saint, Trento, Italy, 2005) pp.340-343.
114. Fuminori Adachi, Takashi Washio and Hiroshi Motoda, Scientific Discovery of Dynamic Hidden States and Differential Law Equations, Proceedings of Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining, SIG-KBS-A403 (JSAI, Hanoi, Vietnam, 2004) pp.175-180.
113. Takashi Washio, Atsushi Fujimoto and Hiroshi Motoda, Extension of Basket Analysis and Quantitative Association Rule Mining, Proceedings of Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining, SIG-KBS-A403 (JSAI, Hanoi, Vietnam, 2004) pp.117-122.
112. Mami Kuroda, Katsutoshi Yada, Hiroshi Motoda and Takashi Washio, Knowledge Discovery from Consumer Behavior in an Alcohol Market by Using Graph Mining Technique, Proceedings of Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining, SIG-KBS-A403 (JSAI, Hanoi, Vietnam, 2004) pp.111-116.
111. Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda and Takashi Washio, Cl-GBI: A Novel Strategy to Extract Typical Patterns from Graph Data, Proceedings of Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining, SIG-KBS-A403 (JSAI, Hanoi, Vietnam, 2004) pp.105-110.
110. Akira Mogi, Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda and Takashi Washio, Analysis of Hepatitis Dataset by Using Cl-GBI, Proceedings of Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining, SIG-KBS-A403 (JSAI, Hanoi, Vietnam, 2004) pp.43-48.
109. Katsutoshi Yada, Hiroshi Motoda, Takashi Washio and Asuka Miyawaki, Consumer Behavior Analysis by Graph Mining Technique, Proceedings of 8th International Conference Knowledge-Based Intelligent Information and Engineering Systems (KES 2004), Part II, LNCS 3214 (Springer, Heidelberg, Germany, 2004) pp.800-806.
108. Phu Chien Nguyen, Takashi Washio, Kouzou Ohara and Hiroshi Motoda, Using a Hash-Based Method for Apriori-Based Graph Mining, Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2004), LNAI 3202 (Springer, Heidelberg, Germany, 2004) pp. 349-361.
107. Takashi Washio, Hideto Yokoi and Katsuhiko Takabayashi, Analysis of Hepatitis Dataset by Decision Tree Graph-Based Induction Kouzou Ohara, Tetsuya Yoshida, Warodom Geamsakul, Hiroshi Motoda, Proceedings of Discovery Challenge Workshop: the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2004) (PKDD, Pisa, Italy, 2004) pp.173-184.
106. Kenichi Yosihda, Fuminori Aadachi, Takashi Washio, Hiroshi Motoda, Teruaki Homma, Akihiro Nakashima, Hiromitsu Fujikawa and Katsuyuki Yamazaki, Density-Based spam detector, Proceedings of KDD International Conference on Knowledge Discovery and Data Mining (SIGKDD2004) (Association for Computing Machinery (ACM), New York, USA, 2004) page 486-493.
105. Hiroshi Motoda, Tetsuya Yoshida, Kouzou Ohara, Warodom Geamsakul, Takashi Washio, Hideto Yokoi and Katsuhiko Takabayashi, Application of DT-GBI to Promoter and Hepatitis Datasets, Proceedings of the Knowledge Discovery in BioMedicine (KDbM-04): the 8thPacific Rim International Conference on Artificial Intelligence (PRICAI2004) (PRICAI, Auckland, New Zealand, 2004) pp.10-40.
104. Tetsuya Yoshida, Warodom Geamsakul, Akira Mogi, Kouzou Ohara, Hiroshi Motoda, Takashi Washio, Hideto Yokoi and Katsuhiko Takabayashi, Preliminary Analysis of Interferon Therapy by Graph-Based Induction, Proceedings of the 3rd International Workshop on Active Mining (AM-2004): the 18th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI-2004) (JSAI, Tokyo, 2004) pp.31-40.
103. Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Atsushi Fujimoto, and Hidemitsu Hanafusa, Development of Generic Search Method Based on Transformation Invariance, Proceedings of 14th International Symposium: Foundations of Intelligent Systems (ISMIS 2003), LNAI 2871 (Springer, Heidelberg, Germany, 2003) pp.486-496.
102. Warodom Geamsakul, Tetsuya Yoshida, Kouzou Ohara, Hiroshi Motoda and Takashi Washio, Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Induction, Working notes of 2nd International Workshop on Active Mining (AM2003) (AM, Maebashi, 2003) pp.106-117.
101. Katsutoshi Yada, Yukinobu Hamuro, Naoki Katoh, Takashi Washio, Issey Fusamoto, Daisuke Fujishima and Takaya Ikeda, Data Mining Oriented CRM Systems Based on MUSASHI: C-MUSASHI, Working notes of 2nd International Workshop on Active Mining (AM2003) (AM, Maebashi, 2003) pp.52-61.
100. Warodom Geamsakul, Takashi Matsuda, Tetsuya Yoshida, Hiroshi Motoda and Takashi Washio, Performance Evaluation of Decision Tree Graph-Based Induction, Proceedings of the 6th International Conference on Discovery Science (DS2003) (Springer, Heidelberg, Germany, 2003) pp.128-140.
99. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, Specific Biases for Mining Frequent Substructures, Proceedings of 1st International Workshop on Mining Graphs, Trees and Sequences (MGTS-2003): ECML/PKDD-2003 (ECML/PKDD, Cavtat-Dubrovnik, Croatia, 2003) pp.45-54.
98. Warodom Geamsakul, Takashi Matsuda, Tetsuya Yoshida, Hiroshi Motoda and Takashi Washio, Constructing a Decision Tree for Graph Structured Data, Proceedings of 1st International Workshop on Mining Graphs, Trees and Sequences (MGTS-2003): ECML/PKDD-2003 (ECML/PKDD, Cavtat-Dubrovnik, Croatia, 2003) pp.1-10.
97. Katsutoshi Yada, Yukinobu Hamuro, Naoki Katoh, Takashi Washio, Issey Fusamoto, Daisuke Fujishima and Takaya Ikeda, Data Mining Oriented CRM Systems Based on MUSASHI: C-MUSASHI, Proceedings of Active Mining: the 2nd International Active Mining Workshop (AM2003), LNAI 3430 (Springer, Heidelberg, Germany, 2003) pp.152-173.
96. Warodom Geamsakul, Tetsuya Yoshida, Kouzou Ohhara, Hiroshi Motoda, Extracting Diagnostic Knowledge from Hepatitis Data by Decision Tree Graph-Based Induction, Proceedings of Active Mining: the 2nd International Active Mining Workshop (AM2003), LNAI 3430 (Springer, Heidelberg, Germany, 2003) pp.126-151.
95. Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida and Takashi Washio, Mining Patterns from Structured Data by Beam-wise Graph-Based Induction, Proceedings of the 6th SANKEN (ISIR) International Symposium, The New Trends in Knowledge Processing – Data Mining, Semantic Web and Computational Science – (2003) pp.98-99.
94. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, General Framework for Frequent Structure Mining, Proceedings of the 6th SANKEN (ISIR) International Symposium, The New Trends in Knowledge Processing – Data Mining, Semantic Web and Computational Science – (2003) pp.85-86.
93. Warodom Geamakul, Takashi Matsuda, Tetsuya Yoshida, Hiroshi Motoda and Takashi Washio, Classifier Construction by Graph-Based Induction for Graph Structured Data, Proc. of the 6th SANKEN (ISIR) International Symposium, The New Trends in Knowledge Processing – Data Mining, Semantic Web and Computational Science – (2003) pp.63-64.
92. Tetsuya Yoshida, Takuya Wada, Hiroshi Motoda and Takashi Washio, Adaptive Ripple Down Rules Method Based on Minimum Description Length Principle, Proceedings of The 2002 IEEE International Conference on Data Mining (ICDM2002) (IEEE, New York, USA, 2002) pp.530-537.
91. Fuminori Adachi, Takashi Washio, Hiroshi Motoda and Hidemitsu Hanafusa, Development of Generic Search Method Based on Transformation Invariance, Working notes of International Workshop on Active Mining: The 2002 IEEE International Conference on Data Mining (ICDM2002) (ICDM, Maebashi, 2002) pp.52-57.
90. Takashi Matsuda, Tetsuya Yoshida, Hiroshi Motoda and Takashi Washio, Active Mining from Hepatitis Data by Beam-Wise GBI, Working notes of International Workshop on Active Mining: The 2002 IEEE International Conference on Data Mining (ICDM2002) (ICDM, Maebashi, 2002) pp.37-44.
89. Akihiro Inokuchi, Takashi Washio, Yoshio Nishimura and Hiroshi Motoda, General Framework for Mining Frequent Patterns in Structure, Working notes of International Workshop on Active Mining: The 2002 IEEE International Conference on Data Mining (ICDM2002) (ICDM, Maebashi, 2002) pp.23-30.
88. Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida and Takashi Washio, Preliminary Analysis of Hepatitis Data by Beam-Wise Graph-Based Induction, Workshop Proceedings of Discovery Challenge (ECML/PKDD-2002) (ECML/PKDD, Helsinki, Finland, 2002) Online Proceedings No.3-1.
87. Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida and Takashi Washio, Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction, Proceedings of the 5th International Conference on Discovery Science (DS2002), LNAI 2534 (Springer, Heidelberg, Germany, 2002) pp.422-429.
86. Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida and Takashi Washio, Knowledge Discovery from Structured Data by Beam-Wise Graph-Based Induction, Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2002), LNAI 2417 (Springer, Heidelberg, Germany, 2002) pp.255-264.
85. Keisei Fujiwara, Tetsuya Yoshida, Hiroshi Motoda and Takashi Washio, Case Generation Method for Constructing an RDR Knowledge Base, Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2002), LNAI 2417 (Springer, Heidelberg, Germany, 2002) pp.228-237.
84. Takuya Wada, Tetsuya Yoshida, Hiroshi Motoda and Takashi Washio, Extension of the RDR Method That Can Adapt to Environmental Changes and Acquire Knowledge from Both Experts and Data, Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2002), LNAI 2417 (Springer, Heidelberg, Germany, 2002) pp.218-227.
83. Takashi Washio and Hiroshi Motoda, Toward the Discovery of First Principle Based Scientific Law Equations, Progress in Discovery Science, Final Report of Japanese Discovery Science Project, State-of the Art Survey, LNAI 2281 (Springer, Heidelberg, Germany, 2002) pp.553-564.
82. Hiroshi Hasegawa, Takashi Washio and Yukari Ishimiya, Inductive Thermodynamics from Time Series Data Analysis, Progress in Discovery Science, Final Report of Japanese Discovery Science Project, State-of the Art Survey, LNAI 2281 (Springer, Heidelberg, Germany, 2002) pp.384-394.
81. Takashi Washio, Conditions of Law Equations and the Approach of their Discovery, Proceedings of International Conference on Advances in Infrastructure for Electronic Business, Education, Science and Medicine on the Internet (SSGRR 2002w) (SSGRR, L’Aquila, Italy, 2002) No.83 (Invited).
80. Takayuki Ikeda, Takashi Washio and Hiroshi Motoda, Basket Analysis on Meningitis Data, Joint JSAI 2001 Workshop Post-Proceedings, LNAI 2253 (Springer, Heidelberg, Germany, 2001) pp.516-524.
79. Takashi Washio and Hiroshi Motoda, A Method to Discover Admissible Model Equations from Observed Data, Working Notes of 4th International Workshop on Similarity Methods (University Stuttgart, Stuttgart, Germany, 2001) pp.231-246.
78. Makoto Tsukada, Takashi Washio and Hiroshi Motoda, Automatic Web-Page Classification by Using Machine Learning Methods, Proceedings of 1st Asia Pacific Conference: Web Intelligence Research and Development (WI2001), LNAI 2198 (Springer, Heidelberg, Germany, 2001) pp.303-313.
77. Takashi Washio, Hiroshi Motoda and Yuji Niwa, Discovering Admissible Simultaneous Equation Models from Observed Data, Proceedings of 12th European Conference on Machine Learning (ECML01), LNAI 2167 (Springer, Heidelberg, Germany, 2001) pp.539-551.
76. Masahiro Terabe, Takashi Washio and Hiroshi Motoda, The Effect of Subsampling Rate on S3 Bagging Performance, Working Notes on Active Learning, Database Sampling, Experimental Design: Views on Instance Selection (ECML/PKDD-2001) (ECML/PKDD, Freiburg, Germany, 2001) Online Proceedings-7.
75. Takashi Washio and Hiroshi Motoda, Discovery of Law Equations Governing Human Affinity under Trade-Off between Cost and Risk, Proceedings of International Meeting of the Psychometric Society (IMPS-2001) (IMPS, Osaka, 2001) pp.74.
74. Takayuki Ikeda, Takashi Washio and Hiroshi Motoda, Basket Analysis on Meningitis Data, Working Notes of JSAI KDD Challenge 2001 (JKDD01) (JSAI, Tokyo, 2001) pp.33-40.
73. Ken Ping Hew, Tetsuo Tomiyama, Takashi Washio and Yasushi Umeda, Language and Algorithm for Synthesis, Proceedings of 2000 International Symposium on Modeling of Synthesis (University of Tokyo, Tokyo, 2000) pp.189-205.
72. Hiroshi Hasegawa, Takashi Washio, Yukari Ishimiya and Takeshi Saito, Nonequilibrium Thermodynamics from Time Series Data Analysis, Proceedings of 3rd International Conference on Discovery Science 2000 (DS2000), LNAI 1967 (Springer, Heidelberg, Germany, 2000) pp.304-305.
71. Takashi Matsuda, Tadashi Horiuchi, Hiroshi Motoda and Takashi Washio, Graph-Based Induction for General Graph Structured Data and Its Application to Chemical Compound Data, Proceedings of 3rd International Conference on Discovery Science 2000 (DS2000), LNAI 1967 (Springer, Heidelberg, Germany, 2000) pp.99-111.
70. Takashi Washio and Hiroshi Motoda, Modeling Admissible Simultaneous Equation Systems Based on Complete Subsets and Scale-Type Constraints, Working notes of Similarity Methods: 3rd International Workshop (University Stuttgart, Stuttgart, Germany, 2000) pp.73-84.
69. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data, Proceedings. of 4th European Conference (PKDD2000), LNAI 1910 (Springer,Heidelberg, Germany, 2000) pp.13-23.
68. Takashi Matsuda, Tadashi Horiuchi, Hiroshi Motoda and Takashi Washio, Extension of Graph-Based Induction for General Graph Structured Data, Proceedings of 4th Pacific-Asia Conference (PAKDD2000), LNAI 1805 (Springer,Heidelberg, Germany, 2000) pp.420-431.
67. Takashi Washio, Hiroshi Motoda and Yuji Niwa, Enhancing the Plausibility of Law Equation Discovery, Proceedings of the 17th International Conference on Machine Learning (ICML2000) (Morgan Kaufmann Publishers, Inc, San Francisco, USA, 2000) pp.1127-1134
66. Akihiro Inokuchi, Takashi Washio, Takashi Okada and Hiroshi. Motoda, Applying Algebraic Mining Method of Graph Substructures to Mutagenesis Data Analysis, Working notes of International Workshop of KDD Challenge on Real-world Data, KDD Challenge 2000, The 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD, Kyoto, Japan, 2000) pp.41-46.
65. Takashi Matsuda, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio, Kouhei Kumazawa and Naohide Arai, Graph-Based Induction for General Graph Structured Data, Proceedings of the 2nd International Conference on Discovery Science (DS’99), LNAI 1721 (Springer, Heidelberg, Germany, 1999) pp.340-342.
64. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, Derivation of the Topology Structure from the Massive Graph Data, Proceedings of the 2nd International Conference on Discovery Science (DS’99), LNAI 1721 (Springer, Heidelberg, Germany, 1999) pp.330-332.
63. Hiroshi Hasegawa, Takashi Washio and Yukari Ishimiya, “Thermodynamics” from Time Series Data Analysis, Proceedings of 2nd International Conference, Discovery Science1999 (DS’99), LNAI 1721 (Springer, Heidelberg, Germany, 1999) pp.326-327.
62. Takashi Washio and Hiroshi Motoda, Extension of Dimensional Analysis for Scale-Types and its Application to Discovery of Admissible Models of Complex Processes, Working Notes of 2nd International Workshop on Similarity Method (University Stuttgart, Stuttgart, Germany, 1999) pp.129-147.
61. Takashi Washio, Hiroshi Motoda and Yuji Niwa, Discovering Admissible Model Equations from Observed Data Based on Scale-Types and Identity Constrains, Proceedings of 16th International Joint Conference on Artificial Intelligence (IJCAI’99) Vol.2 (Morgan Kaufmann Publishers, Inc.,, San Francisco, USA, 1999) pp.772-779.
60. Takashi Washio and Hiroshi Motoda, Automated Scientific Modeling from Observed Data and its Application to Socio-Psychology, Working notes of the 13th International Workshop on Qualitative Reasoning (QR’99) (QR, Loch Awe, Scotland, 1999) pp.240-249.
59. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, Basket Analysis for Graph Structured Data, Proceedings of the 3rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’99), LNAI 1574 (Springer, Heidelberg, Germany, 1999) pp.420-431.
58. Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda and Takashi Washio, Characterization of Default Knowledge in Ripple Down Rules Method, Proceedings of the 3rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’99), LNAI 1574 (Springer, Heidelberg, Germany, 1999) pp.284-295.
57. Masahiro Terabe, Osamu Katai, Tetsuo Sawaragi,Takashi Washio and Hiroshi Motoda,A Data Pre-Processing Method Using Association Rules of Attributes for Improving Decision Tree, Proceedings of the 3rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’99), LNAI 1574 (Springer, Heidelberg, Germany, 1999)pp.143-147.
56. Ken P. Hew, Takashi Washio, Tetsuo Tomiyama and Yasushi Umeda, A Mathematical Theory of Synthesis Design Foundation, Framework, Logic and Application, Proceedings of International Symposium on Modeling of Synthesis (University of Tokyo, Tokyo, 1998) pp.19-31.
55. Takashi Washio and Hirsohi Motoda, Development of SDS2: Smart Discovery System for Simultaneous Equation Systems, Proceedings of Discovery Science (DS98), LNAI 1532 (Springer, Heidelberg,Germany, 1998) pp.352-363.
54. Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda and Takashi Washio, A New Look at Default Knowledge in Ripple Down Rules Method, Proceedings of the 1998 Pacific Rim Knowledge Acquisition Workshop (PKAW’98) (PKAW, Singapore, 1998) pp.171-186.
53. Yuji Niwa, Masahiro Terabe and Takashi Washio, Collaborative Emergency Operation Man-Machine System, Proceedings of 7th IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design and Evaluation of Man-Machine Systems (IFAC-MMS, Kyoto, 1998) pp.461-466.
52. Takashi Washio and Hiroshi Motoda, Discovering Admissible Simultaneous Equations of Large Scale Systems, Proceedings of the 15th National Conference on Artificial Intelligence (AAAI-98) (AAAI, Menlo Park, California, USA, 1998) pp.189-196.
51. Takashi Washio and Hiroshi Motoda, A Watchdog System for Field Quality – A Basket Analysis Approach Satoshi Hori, Yoshitaka Kawashima, Toru Yukimatsu, Hirokazu Taki, Proceedings of US-Japan FA Symposium, Vo.2 (The Japan Society of Mechanical Engineers, Tokyo, 1998) pp.741-748.
50. Takashi Washio, Hiroki Matsuura and Hiroshi Motoda, Mining Association Rules for Estimation and Prediction, Proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’98) (Springer, Heidelberg, Germany, 1998) pp.417-419.
49. Takashi Washio and Hiroshi Motoda, Structured Evaluation Based on Axiomatic Measurement, Working notes of PRESTO “Information and Human Activity” Workshop (PRESTO, Keihanna Plaza, Kyoto, 1998) pp.14-17.
48. Takashi Washio, Hirsohi Motoda, Taiki Kayama and Hiroshi Matsuura, Role of KDD in Autonomous Operation of Large Scale Systems, Proceedings of the International Symposium on Artificial Intelligence, Robotics and Intellectual Human Activity Support for Nuclear Applications (AIR&IHAS, Wako-shi, Saitama, 1997) pp.201-210.
47. Takashi Washio and Hiroshi Motoda, Discovering Admissible Models of Complex Systems Based on Scale-Types and Identity Constraints, Proceedings of 15th International Joint Conference on Artificial Intelligence (IJCAI’97) Vol.2 (Morgan Kaufman Publishers, Inc., San Francisco, USA, 1997) pp.810-817.
46. Tetsuo Tomiyama, Tamotsu Murakami, Takashi Washio, Akihiro Kubota, Hideaki Takeda, Takashi Kiriyama, Yasushi Umeda, and Masaharu Yoshioka, The Modeling of Synthesis – From the Viewpoint of Design Knowledge, Proceedings of International Conference on Engineering Design (ICED’97), Vol.3 (ICED, Tampere, Finland, 1997) pp.97-100.
45. Hiroshi Motoda, Takashi Washio, Taiki Kayama and Kennichi Yoshida, Extracting Behavioral Patterns from Relational History Data, Working Notes of the Workshop on Machine Learning for User Modeling with Sixth International Conference on User Modeling (ICUM, Chia Laguna, Sardinia, Italy, 1997) pp.6.1-6.6.
44. Makoto Takahashi, Koutarou Fukui, Takashi Washio and Masaharu Kitamura, Information Provision System for Maintenance Support Based on Augmented Reality and Network Computing, Proceedings of International Conference on Maintenance and Reliability (MARCON 97), Vol.2 (University of Tennessee, Knoxville Tennessee, USA, 1997) pp.64.01-64.10.
43. Takashi Washio and Hiroshi Motoda, Discovery of First Principle Based on Data-Driven Reasoning, Proceedings of the 1st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’97) (World Scientific, Singapore, 1997) pp.169-182.
42. Takashi Washio and Masaharu Kitamura, Identification of Hidden Factors in Subjective Evaluation of Man-Machine Interface, Proceedings of Cognitive Systems Engineering in Process Control (CSEPC’96) (Atomic Energy Society of Japan and Graduate School of Energy Science, Kyoto University, 1996) pp.172-175.
41. Yuji. Niwa, Takashi Washio and Masahiro Terabe, An Agent-Based Emergency Operating Procedure in Nuclear Power Plant, Proceedings of Cognitive Systems Engineering in Process Control (CSEPC’96) (Atomic Energy Society of Japan and Graduate School of Energy Science, Kyoto University, 1996) pp.107-113.
40. Takashi Washio and Hiroshi Motoda, Discovery of Possible Law Formulae Based on Measurement Scale, Proceedings of the 4th International Workshop on Rough Sets, Fuzzy Sets and Machine Discovery (IPSJ, Tokyo, 1996) pp.209-216.
39. Takashi Washio and Hiroshi Motoda, Discovery of Possible Law Equations by Combined Use of Scale-Based and Data-Driven Reasoning, Working Note of the Pacific Knowledge Acquisition Workshop (PKAW’96) (University of New South Wales, Sydney, Australia, 1996) pp.130-149.
38. Takashi Washio, Junnichi Okusa and Aakira Endou, Intelligent Virtual Measurements in a Process Plant Based on Model-based Diagnosis, Working Notes of 7h International Workshop on Principles of Diagnosis (DX-96) (DX, Val Morin, Canada, 1996) pp.249-257.
37. Takashi Washio, Hiroshi Motoda and Masaharu Kitamura, Decision Process Modeling Based on Consensus Among Fuzzy Integral and AHP, Proceedings of the 4th International Conference on Soft Computing, Vol.1 (World Scientific, Singapore, 1996) pp.308-311.
36. Takashi Washio and Hiroshi Motoda, A History-Oriented Envisioning Method, Proceedings of 4th Pacific Rim International Conference on Artificial Intelligence (PRICAI’96), LNAI 1114 (Springer, Heidelberg, Germany, 1996) pp. 312-323.
35. Masahiro Terabe, Takashi Washio, Oosamu Katai and Tetsuo Sawaragi, A Study of Organization Learning in Multiagent Systems, Working Notes of Workshop on Learning in Distributed Artificial Intelligence Systems (ECAI’96 Workshop) (ECAI, Budapest, Hungary, 1996) pp.110-119.
34. Takashi Washio and Hiroshi Motoda, Scale-Based Reasoning on Possible Law Equations, AAAI Technical Report: Qualitative Reasoning, The 10th International Workshop (QR’96) (AAAI Press, Menlo Park, California, USA, 1996) pp.255-264.
33. Takashi Washio and Masaharu Kitamura, Worm-Type Agents for Intelligent Operation of Large-Scale Man-Machine Systems, Proceedings of 6th International Conference on HUMAN-COMPUTER INTERACTION (Symbiosis of Human and Artifact) (HCI International’95) (Elsevier Science B.V., Amsterdam, the Netherland,1995) pp.925-930.
32. Masaharu Kitamura, Hiroshi Furukawa, Robert Kozma and Takashi Washio, Guiding Rules for Development of Intelligent Monitoring System of Nuclear Power Plants, Proceedings of a Symposium on Nuclear Reactor Surveillance and Diagnostics (SMORN VII) (SMORN, Knoxville, Tennessee, USA, 1995) pp.14.5.1-14.5.9.
31. Takashi Washio and Masaharu Kitamura, A Fast History-Oriented Envisioning Method Introducing Temporal Logic, Working Papers of the 9th International Workshop on Qualitative Reasoning about Physical Systems (QR’95) (University of Amsterdam, Amsterdam, the Netherland, 1995) pp.279-288.
30. Takashi Washio and Masaharu Kitamura, Towards a Theory of Diversity-Based Diagnosis, Working Papers of the 5th International Workshop on Principles of Diagnosis (DX-94) (DX, New Paltz, USA, 1994) pp.352-356.
29. Takashi Washio, A History-Oriented Envisioning Method, Working Papers of the 8th International Workshop on Qualitative Reasoning about Physical Systems (QR’94) (QR, Nara, Japan, 1994) pp.286-294.
28. Masaharu Kitamura, Hiroshi Furukawa, Masatake Sakuma, Robert Kozma and Takashi Washio, Robust Diagnosis of Nuclear Plant Anomalies through Multiple Neuro-Agent Cooperation, Transaction of American Nuclear Society, Vol.70 (American Nuclear Society, La Grange Park, Illinois, USA, 1994) pp.105-107.
27. Takashi Washio, Masatake Sakuma and Masaharu Kitamura, A Diagnosis Method for Multiple Failures in a Nonlinear and Dynamic Process, Proceedings of 10th Canadian Conference on Artificial Intelligence (AI’94) (Morgan Kaufman Publishers, Inc., Palo Alto, California, 1994) pp.139-146.
26. Masaharu Kitamura, Hiroshi Furukawa, Masatake Sakuma and Takashi Washio, Diversity and Consensus as Key Concepts for Design of Intelligent Operator Support System, Proceedings of the 4th International Topical Meeting on Nuclear Thermal Hydraulics, Operations and Safety (Nuclear Energy Society, Taipei, Taiwan, 1994) pp.41-C-1 – 41-C-8.
25. Masaharu Kitamura, Keiji Kuchimura, Hiroshi Furukawa and Takashi Washio, Advanced Diagnosis of Complex Dynamic Systems through Consensus Formation among Multiple Neural Networks, Proceedings of Artificial Neural Networks in Engineering (ANNIE’93) Vol.3 (ASME Press, New York, USA, 1993) pp.641-648.
24. Masaharu Kitamura, Hiroshi Furukawa, Masatake Sakuma and Takashi Washio, Combining Advisory and Credibility Information as Communication Message from Intelligent Machine for Efficient Man-Machine Cooperation, Proceedings of 2nd IEEE International Workshop on Robot and Human Communication (RO-MAN’93) (IEEE, New York, USA,, 1993) pp.253-258.
23. Takashi Washio, Masatake Sakuma and Masaharu Kitamura, A Diagnosis Method for Multiple Process Failures, Working Papers of the 4th International Workshop on Principles of Diagnosis(DX-93) (University College of Wales, Aberystwyth, UK, 1993) pp.327-340.
22. Masaharu Kitamura, Hiroshi Furukawa, Keiji Kuchimura and Takashi Washio, Diversification of Symptom Description and Causal Reasoning for Higher Credibility of Computer-Assisted Diagnosis in Nuclear Plants, Proceedings of the Topical Meeting on Nuclear Plant Instrumentation, Control,and Man-Machine Interface Technologies (American Nuclear Society, La Grange Park, Illinois, USA, 1993) pp.427-434.
21. Ryousuke Takahashi, Akiyuki Kameda and Takashi Washio, Fuzzy Evaluation Methodology for Man-Machine Task Allocation, Proceedings of Post ANP’92 Conference Seminaron Human Cognitive and Cooperative Activities in Advanced Technological Systems (Kyoto University, Kyoto, 1992) pp.13-24.
20. Takashi Washio, Hideaki Takahashi and Masaharu Kitamura, A Method for Supporting Decision-Making on Plant Operation Based on Human Reliability Analysis with Fuzzy Integral, Proceedings of the 2nd International Conference on Fuzzy Logic and Neural Networks (IIZUKA’92), Vol.2 (FLSI, Iizuka, Fukuoka, 1992) pp.841-845.
19. Takashi Washio and Masaharu Kitamura, A New Approach to Plant Component Diagnosis Based on Credible and Transparent Physical Knowledge, Proceedings of 8th Power Plant Dynamics, Control & Testing Symposium., Vol.1(University of Tennessee, Knoxville, Tennessee, 1992) pp.15.01-15.16.
18. Takashi Washio and John A. Bernard, Stability Considerations Concerning the Implementation of the MIT-SNL Period-Generated Minimum Time Control Laws, Proceedings of Space Nuclear Power Systems 1989 (Orbit Book Co., Malabar, Florida, USA, 1992) pp.393-404.
17. John A. Bernard, Kwon S. Kwok and Takashi Washio, Frank J. Wyant and Frank V. Thome, Experimental Demonstration of the MIT-SNL Period-Generated Minimum Time Control Laws for Rapid Increases of Reactor Power from Subcritical Conditions, Proceedings of Space Nuclear Power Systems 1989 (Orbit Book Co., Malabar, Florida, USA, 1992) pp.381-392.
16. Takashi Washio, Yutaka Kitamura, Hideaki Takahashi and Masaharu Kitamura, Decision Support for Operability Improvement and Maintenance Planning by Analytic Hierarchy Process Methodology, Proceedings of International Conference on Probabilistic Safety Assessment and Management (PSAM), Vol.2 (Elsevier Science Publishing Co. Inc., New York, USA,1991) pp.1451-1456.
15. Takashi Washio, Development of a Quantitative and Symbolic Causal Reasoning Method for Spacecraft Nuclear Reactors, Proceedings of the 7th Symposium on Space Nuclear Power Systems CONF-900109. (Orbit Book Co., Malabar, Florida, USA, 1990) pp.968-975.
14. Shing H. Lau, Takashi Washio, Kwon S. Kwok, John A. Bernard, David D. Lanning and Frank J. Wyant, A Methodology for the Control of Core Average Temperature in Spacecraft Nuclear Reactors, Proceedings of the 7th Symposium on Space Nuclear Power Systems CONF-900109. (Orbit Book Co., Malabar, Florida, USA, 1990) pp.956-961.
13. Takashi Washio, Derivation of Exogenously-Driven Causality Based on Assumptive Structural Equations, Working Papers of QR’89: The Third International Workshop on Qualitative Reasoning (Stanford Univ., San Francisco, USA, 1989).
12. John A. Bernard and Takashi Washio, The Utilization of Expert Systems within the Nuclear Industry, Proceedings of the American Control Conference, Vol.1 (ACC, Pittsburgh, Pennsylvania, USA, 1989) pp.373-378.
11. Masaharu Kitamura, Takashi Washio, Toshimitsu Baba and Kazusuke Sugiyama, Evaluation of Signal Importance for Effective Implementation of Functional Redundancy, Proceedings of Computing and Computers for Control Systems (IMACS) (J. C. Baltzer AG Scientific Publishing Co., Basel, Switzerland, 1989) pp.315-317.
10. Takashi Washio and John A. Bernard, Stability Considerations and Noise Reduction in the Implementation of the MIT-SNL Period-Generated Minimum Time Control Laws, Proceedings of the 6th Symposium on Space Nuclear Power Systems CONF-890103-Summs. (Orbit Book Co., Malabar, Florida, USA, 1989) pp.476-479.
9. John A. Bernard, Kwon S. Kwok, Takashi Washio, Frank J. Wyant and Frank V. Thome, Proceedings of the 6th Symposium on Space Nuclear Power Systems CONF-890103-Summs. (Orbit Book Co., Malabar, Florida, USA, 1989) pp.466-469.
8. John A. Bernard, Kwon S. Kwok and Takashi Washio, Autonomous Control of Spacecraft Nuclear Reactors, Proceedings of SPIE Conference: Space Station Automation IV SPIE., Vol.1006(SPIE, Bellingham, Washington, USA, 1988) pp.28-45.
7. John A. Bernard and Takashi Washio, An Examination of Expert Systems Activities within the Nuclear Industry, Transaction of American Nuclear Society, Vol.57 (American Nuclear Society, La Grange Park, Illinois, USA, 1988) pp.240-241.
6. Takashi Washio and John A. Bernard, Development and Experimental Demonstration of a Noise Reduction Technique for a Non-Linear Dynamic System, Transaction of American Nuclear Society, Vol.57 (American Nuclear Society, La Grange Park, Illinois, USA, 1988) pp.96-97.
5. Takashi Washio, Masaharu Kitamura and Kazusuke Sugiyama, A Method of Failure Diagnosis Based on Time-Domain Failure Symptoms, Transaction of American Nuclear Society: 13th Biennial Conference on Reactor Operating Experience & International Meeting on Nuclear Power Plant Operation, Vol.54, Suppl.1 (American Nuclear Society, La Grange Park, Illinois, USA, 1987) pp.148-149.
4. Masaharu Kitamura, Toshimitsu Baba, Takashi Washio and Kazusuke Sugiyama, Development of Knowledge Base System for Assisting Signal Validation Scheme Design, Proceedings of the Topical Meeting “Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry: Present and Future” (Plenum Press, New York and London, USA and UK, 1987) pp.141-147.
3. Takashi Washio, Masaharu Kitamura, Kyuya Kotajima and Kazusuke Sugiyama, Automated Generation of Nuclear Power Plant Safety Information (Qualitative Simulation and Derivation of Failure Symptom Knowledge), Proceedings of 6th Power Plant Dynamics, Control & Testing Symposium, Vol.1 (University of Tennessee, Knoxville, Tennessee, 1986) pp.39.01-39.17.
2. Masaharu Kitamura, Takashi Washio, Kyuya. Kotajima and Kazusuke Sugiyama, Advanced Techniques of Time Series Analysis for Reactor Surveillance and Diagnosis, Proceedings of 6th Power Plant Dynamics, Control & Testing Symposium, Vol.1 (University of Tennessee, Knoxville, Tennessee,1986) pp.23.01-23.18.
1. Takashi Washio, Masaharu Kitamura, Kyuya Kotajima and Kazusuke Sugiyama, Semantic Network Approach to Automated Failure Diagnosis in Nuclear Power Plant, Proceedings of ANS International Topical Meeting on Computer Applications for Nuclear Power Plant Operation and Control, American Nuclear Society (La Grange Park, Illinois, USA, 1985) pp.654-661.
解説・総説
42. 鷲尾 隆, 機械学習と先端計測の共進化 -論点と成果-, 計測インフォマティクス：情報科学による計測技術の深化－４, 電気学会誌, Vol.141, No.6 (2021) pp.340-344.
41. 鷲尾 隆, はじめに, 計測インフォマティクス：情報科学による計測技術の深化－１, 電気学会誌, Vol.141, No.6 (2021) pp.328-329.
40. 谷口正輝, 鷲尾 隆, ナノポアデバイスと機械学習で疾病を”診る”, 電気学会誌，Vol.141, No.8 (2021) pp.512-515.
39. 南 皓輔, 根本尚大, 今村 岳, 柴 弘太, 田村 亮, 鷲尾 隆, 吉川元起, 嗅覚センサの実現に向けたMSS とデータ解析技術の融合, 特集：先端技術のつくり出す嗅覚世界―AIや新技術と香り・におい, AROMA RESEARCH フレグランスジャーナル社, No.80 (Vol.20 No.4) (2019) pp.312-317.
38. 和沢鉄一, 鷲尾 隆, 永井健治, 回転偏光照明蛍光顕微鏡と光スイッチング蛍光タンパク質を用いた超解像イメージング法：SPoD-OnSPAN, 光アライアンス 日本工業出版, Vol.30, No.8 (2019) pp.15-19.
37. 今村 岳, 吉川元起, 鷲尾 隆, においデータの解析方法と新たな展開─ポンプレス嗅覚センサに向けて, におい・かおり環境学会誌, Vol.49, No. 5 (2018) pp.315-322.
36. 鷲尾 隆, 機械学習とその化学研究への展望, 現代化学 ３月号, 東京化学同人, No.552 (2017) pp.53-56.
35. 安並 一浩, 井上 剛, 鷲尾 隆, 太陽光発電出力変動分析のための日射強度推定技術, 電子情報通信学会誌，Vol.95, No.10 (2012) pp.885-888.
34. 河原 吉伸, 永野清仁, 鷲尾 隆, 劣モジュラ性に基づく知能情報処理への新展開, 人工知能学会誌，Vol.27, No.3 (2012) pp.252-260. 33. 鷲尾 隆, 情報爆発時代の高次元データマイニング, 電子情報通信学会誌, Vol.94, No.8 (2011) pp.679-683.
32. 樋口 知之, 鷲尾 隆, 「特集 データマニングと統計数理」について, 統計数理, Vol.56, No.2 (2008) pp.167-168.
31. 鷲尾 隆, 一流国際会議発表のための研究戦略とは？, 人工知能学会誌, Vol.23, No.3 (2008) pp.362-366.
30. 鷲尾 隆, 因果関係モデリングにおけるデータマイニング・グラフマイニング技術の活用, 日本化学学会情報化学部会誌, Vol.25, No.3 (2007) pp.76-80.
29. 鷲尾 隆, データインテンシブコンピューティング その１ 離散構造マイニング, 人工知能学会誌, Vol.22, No.2 (2007) pp.263-271.
28. 鷲尾 隆, 離散構造データからの完全探索による知識発見, 計測と制御, Vol.44 (2005) pp.307-312.
27. 元田 浩, ホーツーバオ, 鷲尾 隆, 矢田勝俊, 吉田哲也, 大原剛三, 構造データからのアクティブマイニング, 人工知能学会誌, Vol.20, No.2 (2005) pp.172-179.
26. 羽室行信, 加藤直樹, 矢田勝俊, 鷲尾 隆, 大規模ビジネスデータからの知識発見システム：ＭＵＳＡＳＨＩ, 人工知能学会誌, Vol.20, No.1 (2005) pp.59-66.
25. 鷲尾 隆, グラフベースデータマイニングの基礎と現状, 情報処理学会誌, Vol.46, No.1 (2005) pp.20-26.
24. 鷲尾 隆, データマイニング実践家達の声：第１回 データマイニング実用化：概観と展望, 人工知能学会誌, Vol.19, No.3 (2003) pp.373-375.
23. Takashi Washio and Hiroshi Motoda, State of the Art of Graph-based Data Mining, ACM, SIGKDD Explorations, Vol.5, Issue 1 (2003) pp.59-68.
22. 羽室行信, 加藤直樹, 矢田勝俊, 鷲尾 隆, MUSASHIでらくらくデータマイニング, Software Design, 2003年10月号 (2003) pp.83-91.
21. 丹羽雄二, 鷲尾 隆, 元田 浩, 尺度制約による複雑系, 社会系のモデリングとその応用の提案, ヒューマンインターフェース学会研究報告集, Vol.4, No.2 (2002) pp.1-8.
20. 元田 浩, 鷲尾 隆, データマイニング展望, システム／制御／情報, Vol.46, No.4 (2002) pp.1-8.
19. 鷲尾 隆, 観測データからの科学法則式の発見, 計測と制御, Vol.41, No.5 (2002) pp.319-324.
18. 鷲尾 隆, ビジネスにおけるデータマイニングの現在・未来, 情報処理, Vol.42, No.5 (2001) pp.467-471.
17. 鷲尾 隆, 法則式発見理論での数理モデル, 人工知能学会誌, Vol.16, No.2 (2001) pp.245-248.
16. 鷲尾 隆, 元田 浩, 計算機による法則式発見への挑戦, 応用数理, Vol.11, No.1 (2001) pp.59-62.
15. 鷲尾 隆, 元田 浩, 構造データ及び数値データに対する相関ルールマイニングの拡張, 人工知能学会誌, Vol. 15, No. 5 (2000) pp.759-767.
14. 元田 浩，鷲尾 隆，鈴木 英之進，寺野 隆雄，津本 周作，山口 高平, 第4回太平洋アジア地域知識発見とデータマイニング国際会議の報告, 人工知能学会全国大会（第14回）論文集, (2000) pp.84-86.
13. 鷲尾 隆, 構造化データに関するマイニング技術の変遷と展望, 人工知能学会全国大
（第14回）論文集 (2000) pp.93-96.
12. 鷲尾 隆, 法則式発見理論での数理モデル, 人工知能学会全国大会（第14回）論文集 (2000) pp.32-33.
11. Hiroshi Motoda and Takashi Washio, Discovery of Laws, IEICE Transactions on Information and Systems, Special Issue on Surveys on Discovery Science, Vol.E83-D, No.1 (2000) pp.44-51.
10. 丹羽雄二, 寺邊正大, 鷲尾 隆, ソフトウエア・エージェントによる原子力発電プラントの事故時自動操作系の概念設計に関する研究, INSS Journal: Journal of the Institute of Nuclear Safety System, No.6 (1999) pp.176-187.
9. 大草 亨一, 鷲尾 隆, 二次系ナトリウム流量計測における仮想測定技術の開発, サイクル機構技報, No.3 (1999) pp.1-8.
8. 鷲尾 隆, 進化する診断技術:人間・機械協調の新しいパラダイムを目指して:モデルベース診断, 日本原子力学会誌, Vol.40, No.9 (1998) pp.664-667.
7. 鷲尾 隆, モデルベース診断, 日本原子力学会会誌, Vol.40, No.9 (1998) pp.664-667.
6. 鷲尾 隆, 元田 浩, 尺度の理論, 日本ファジィ学会誌, Vol.10, No.3 (1998) pp.401-413.
5. 元田 浩, 鷲尾 隆, 機械学習とデータマイニング, 人工知能学会誌, Vol.12, No.4 (1997) pp.505-512.
4. Makoto Shimamura, Hiroshi Fukuyama and Takashi Washio, A Study on Strong Wind Predicting Technique for Safety Management of Train Operation, Japanese Railway Engineering, No.134 (1995) pp.15-18.
3. 鷲尾 隆, 人間信頼性へのファジィ積分の応用, 日本ファジィ学会誌, Vol.5, No.5 (1993) pp.958-969.
2. 鷲尾 隆, 北村 豊, 高橋英明, ファジイ理論を用いた人間信頼性解析手法の開発, 三菱総合研究所 所報NO.18 (1990) pp.104-119.
1. Takashi Washio, Causal Ordering Methods Based on Physical Laws of Plant Systems, Laboratory Report, Report No.MITNRL-033, Nuclear Reactor Laboratory, Massachusetts Institute of Technology (MIT) (1989).
著書
- 36. 鷲尾隆, AI・ナノ・量子による超高感度・迅速バイオセンシング -超早期パンデミック検査・超早期診断・POCTから健康長寿社会へ, AIが実現する超高精度・ロバストなバイオセンシング・デバイス (第Ⅰ編第２章), 馬場嘉信, 柳田剛, 加地範匡, 第Ⅰ編第２章, シーエムシー出版 (2021).
- 35. Makusu Tsutsui, Takeshi Yanagida, Takashi Washio, and Tomoji Kawai, Handbook of Single Cell Technologies, Micro- and Nanopore Technologies for Single-Cell Analysis (Chapter 15), Tuhin Subhra Santra and Fan-Gang Tseng, Chapter 15 pp.43-373, Springer (2020).
- 34. Tetsuichi Wazawa, Takashi Washio and Takeharu Nagai, Single Molecule Microscopy in Neurobiology, Highly Biocompatible Super-resolution Imaging: SPoD-OnSPAN, Nobuhiko Yamamoto and Yasushi Okada, Chapter 11 pp.29-244, Springer Nature (2020).
- 33. 鷲尾隆, ビッグデータ・マネージメント データサイエンティストのためのデータ利活用技術と事例, ビッグデータからのモデリング手法 (第2章第4節), 嶋田茂, 第2章第4節pp.57-67, エヌ・ティ・エス社 (2014).
- 32. Takashi Washio and Jun Luo, Emerging Trends in Knowledge Discovery and Data Mining: PAKDD 2012 International Workshops: DMHM, GeoDoc, 3Clust, and DSDM, Springer, Vol.LNAI7769 (2013).
- 31. Takashi Washio, Advances in Machine Learning, Advances in Machine Learning, Proc. of First Asian Conference on Machine Learning, ACML 2009, Lecture Notes in Computer Science (LNCS), Lecture Notes in Artificial Intelligence (LNAI) (2009) Vol.5828.
- 30. Takashi Washio, Special Issue on Data-Mining and Statistical Science, New Generation Computing, Computing Paradigms and Computational Intelligence, Guest Editor T. Washio, Vol.27 (2008) No.4.
- 29. Sanjay Chawla, Takashi Washio, Shin-ichi Minato, Shusaku Tsumoto, Takashi Onoda, Seiji Yamada and Akihiro Inokuchi, New Frontiers in Applied Data Mining, PAKDD 2008 International Workshop, Osaka, Japan, May 20-23, 2008, Revised Selected Papers, LNCS: Lecture Notes in Computer Science, LNAI: Lecture Notes in Artificial Intelligence, Vol.5433 (2008)
- 28. Kenta Fukata, Takashi Washio, Katsutoshi Yada and Hiroshi Motoda, A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis, Data Mining for Design and Marketing, Edited by Yukio Osawa and Katsutoshi Yada, CRC Press, Taylor & Francis Corp., Chapter 5 (2009) pp.81-94.
- 27. Tomoyuki Higuchi and Takashi Washio (Eds.), Featured section on data mining and statistical science, Annals of the Institute of Statistical Mathematics, Vol.60, No.4 (2008)
- 26. Takashi Washio, Einoshin Suzuki, Kai Ming Ting and Akihiro Inokuchi (Eds.), Advances in Knowledge Discovery and Data Mining, Proc. of 12th Pacific-Asia Conference of Knowledge Discovery and Datamining, PAKDD 2008, Lecture Notes in Computer Science (LNCS) Vol. 5012, Springer, Berlin, Heidelberg, New York (2008)
- 25. Carlos Soares, Younghong Peng, Jun Meng, Takashi Washio and Zhi-Hua Zhou, Applications of Data Mining in E-Business and Finance, Frontiers in Artificial Intelligence and Applications, No.177, IOS Press (2008)
- 24. 鷲尾 隆 他：国友 直人，山本 拓監修，小西 貞則，国友 直人編, 21世紀の統計科学 － 自然・生物・健康の統計科学 － 第10章 グラフマイニングとその統計的モデリングへの応用, 東京大学出版会，第10章（2008）pp.291-314.
- 23. Takashi Washio and Shusaku Tusmoto, International Workshop on Risk Informatics (RI2007), Post Proc. of JSAI 2007 Conference and Workshop, Miyazaki, Japan, June, 2007: New Frontiers in Artificial Intelligence, LNAI 4914 (2008) pp.245-246
- 22. Takashi Washio, et al. (Eds), Emerging Technologies in Knowledge Discovery and Data Mining, Lecture Notes in Artificial Intelligence (LNAI), Lecture Notes in Computer Science (LNCS), Vol.4819, ISBN: 978-3-540-77016-9, Springer (2007)
- 21. Takashi Washio and Hiroshi Motoda, Communicability Criteria of Law Equation Discovery, Computational Discovery of Scientific Knowledge, Introduction, Techniques and Applications in Environmental and Life Sciences, LNAI 4660, Springer (2007) pp.98-119.
- 20. Takashi Washio, Special Issue: Applications eligible for data mining, Advanced Engineering Informatics, Vol.21 (2007) pp.241-301.
- 19. 鷲尾 隆, 設計知識の高度処理：データマイニング，知識発見，機械工学便覧，デザイン編β１，設計工学, 日本機械学会編，５・３・３（第５章３節３項）ａ－ｄ(2007) pp.202-205.
- 18. Kouzou Ohara, Phu Chien Nguyen, Akira Mogi, Hiroshi Motoda and Takashi Washio, Constructing Decision Tree Based on Chunkingless Graph-Based Induction, Mining Graph Data, Eds: Diane J. Cook and Lawrence B. Holder, Chap.8,Wiley-Interscience, A John Wiley & Sons, Inc. (2007) pp.203-226.
- 17. Kiyoto Takabayashi, Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoa and Takashi Washio, Extracting Discriminative Patterns from Graph Structured Data using Constrained Search, Advances in Knowledge Acquisition and Management, Pacific Rim Knowledge Acquisition Workshop, PKAW 2006, Revised Selected Papers, LNAI 4303 (2006) pp.64-74.
- 16. Takashi Washio, Akito Sakurai, Katsuto Nakajima, Hideaki Takeda, Satoshi Tojo and Makoto Yokoo (Eds.), New Frontiers in Artificial Intelligence, Joint JSAI 2005 Workshop Post-Proceeding, Lecture Notes in Computer Science(LNCS), Springer Berlin/Heidelbergs, ISSN: 0302-97433, Subject: Computer Science, LNAI 4012 (2006)
- 15. Takashi Washio, Ken Satoh, Hideaki Takeda and Akihiro Inokuchi (Eds.), New Frontiers in Artificial Intelligence, JSAI 2006 Conference and Workshop, Tokyo, Japan, June 2006, Revised Selected Papers, New Frontiers in Artificial Intelligence, LNAI 4384, Springer (2006)
- 14. 鷲尾 隆, 人工知能学時点，13-1 知識発見のプロセス，13-2 科学的発見，13-15 構造マイニング，13-d AssociationとCorrelation, 人工知能学会編 (2006) pp.656, pp.659-660, pp.661-662, pp.681-682.
- 13. Takashi Washio, Akito Sakurai, Katsuto Nakajima, Hideaki Takeda, Satoshi Tojo and Makoto Yokoo (Eds.), New Frontiers in Artificial Intelligence, Proceedings of the 19th Annual Conference of the Japanese Society for Artificial Intelligence, JSAI 2005 Workshops, LNAI 4012, Springer-Verlag (2006).
- 12. Takashi Washio and Hiroshi Motoda, Data Mining and Knowledge Discovery Handbook, C5.4.1 – Methodology for Equation Fitting, Springer, ISBN: 0387244352 (2005) pp.368-375.
- 11. 鷲尾 隆, 人工知能学辞典, 13-1 知識発見のプロセス, 13-2 科学的発見, 13-15 構造マイニング, 13-d AssociationとCorrelation, 人工知能学会編 (2006) pp.656, pp.659-660, pp.661-62, pp.681-682.
- 10. Takashi Washio, Joost .N. Kok and Luc De Raedt (Eds), Advances in Mining Graphs, Trees and Sequences, Frontiers in Artificial Intelligence and Applications, IOS Press (2005).
- 9. Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda, A General Framework for Mining Frequent Subgraphs from Labeled Graphs, Advances in Mining Graphs, Trees and Sequences, Frontiers in Artificial Intelligence and Applications, IOS Press (2005) pp.53-82.
- 8. 鷲尾 隆, 知識マネジメント, 4.1節, 5.1節, IT Text, IPS 情報処理学会編集, オーム社 pp.77-84 (2003) pp.117-124.
- 7. Takashi Washio and Hiroshi Motoda, Handbook of Data Mining and Knowledge Discovery, C5.4.1 – Methodology for Equation Fitting, Oxford Univ Press (2002) pp.368-375.
- 6. Takao Terano, Toyoaki Nishida, Akira Namatame, Syrusaku Tsumoto, Yukio Ohsawa and Takashi Washio (Eds), New Frontiers in Artificial Intelligence: Joint JSAI 2001 Workshop Post-Proceedings, LNAI 2253 (2002)
- 5. 鷲尾 隆, 組織知識管理とデータマイニング:安全の探究「人・社会と巨大技術が構成するシステムの安全学とその実践」, 第６章 (2001) pp.159-178.
- 4. 鷲尾 隆, 元田 浩, 発見科学とデータマイニング: 第２１章 計算機による 科学的法則・モデルの発見方法の展開, bit別冊 発見科学とデータマイニング (2000) pp.207-216.
- 3. 鷲尾 隆, 知能工学概論 第２章 エージェント, 昭晃堂 (1996) pp.27-42.
- 2. Takashi Washio and Masaharu Kitamura, Human Reliability Analysis with Fuzzy Integral, Reliability and Safety Analyses under Fuzziness (Chap.6), Physica-Verlag Heidelberg (1995) pp.233-244.
- 1. John A. Bernard and Takashi Washio, Expert Systems Applications within the Nuclear Industry, American Nuclear Society (ANS), ISBN: 0894480340 (1989)