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Washio Takashi

鷲尾 隆

The Institute of Scientific and Industrial Research, Professor

Research Areas

  • Informatics, Intelligent informatics

Papers

  • 【ナノポア応用研究の最前線】AIと固体ナノポアセンサによるウイルス検査, 有馬 彰秀,筒井 真楠,鷲尾 隆,馬場 嘉信,川合 知二, 生物工学会誌, (公社)日本生物工学会, Vol. 101, No. 8, p. 439-442, 2023/08
  • Bayesian Optimization-Assisted Screening to Identify Improved Reaction Conditions for Spiro-Dithiolane Synthesis, Masaru Kondo,Hettiarachchige Dona Piyumi Wathsala,Kazunori Ishikawa,Daisuke Yamashita,Takeshi Miyazaki,Yoji Ohno,Hiroaki Sasai,Takashi Washio,Shinobu Takizawa, Molecules, MDPI AG, Vol. 28, No. 13, p. 5180-5180, 2023/07/03
  • Predicting heart failure onset in the general population using a novel data-mining artificial intelligence method, Yohei Miyashita,Tatsuro Hitsumoto,Hiroki Fukuda,Jiyoong Kim,Takashi Washio,Masafumi Kitakaze, Scientific Reports, Springer Science and Business Media LLC, Vol. 13, No. 1, 2023/03/16
  • Electrochemical Carbon-Ferrier Rearrangement Using a Microflow Reactor and Machine Learning-Assisted Exploration of Suitable Conditions, Eisuke Sato,Gaku Tachiwaki,Mayu Fujii,Koichi Mitsudo,Takashi Washio,Shinobu Takizawa,Seiji Suga, Organic Process Research & Development, 2023/01/27
  • Bayesian optimization-driven parallel-screening of multiple parameters for the flow synthesis of biaryl compounds, Masaru Kondo,H. D.P. Wathsala,Mohamed S.H. Salem,Kazunori Ishikawa,Satoshi Hara,Takayuki Takaai,Takashi Washio,Hiroaki Sasai,Shinobu Takizawa, Communications Chemistry, Vol. 5, No. 1, 2022/12
  • Isolation Kernel Estimators, Kai Ming Ting,Takashi Washio,Jonathan Wells,Hang Zhang,Ye Zhu, Knowledge and Information Systems, Springer Science and Business Media LLC, 2022/10/01
  • Identification of Bacterial Drug-Resistant Cells by the Convolutional Neural Network in Transmission Electron Microscope Images, 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,Kunihiko Nishino, Frontiers in Microbiology, Frontiers Media SA, Vol. 13, 2022/03/15
  • Search strategy for rare microstructure to optimize material properties of filled rubber using machine learning based simulation, Takashi Kojima,Takashi Washio,Satoshi Hara,Masataka Koishi, Computational Materials Science, Elsevier BV, Vol. 204, p. 111207-111207, 2022/03
  • Bayesian optimization with constraint on passed charge for multiparameter screening of electrochemical reductive carboxylation in a flow microreactor, Yuki Naito,Masaru Kondo,Yuto Nakamura,Naoki Shida,Kazunori Ishikawa,Takashi Washio,Shinobu Takizawa,Mahito Atobe, CHEMICAL COMMUNICATIONS, ROYAL SOC CHEMISTRY, Vol. 58, No. 24, p. 3893-3896, 2022/03
  • Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection, 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,Kazunori Tomono, Nature Communications, Springer Science and Business Media LLC, Vol. 12, No. 1, 2021/12
  • Field effect control of translocation dynamics in surround-gate nanopores, Makusu Tsutsui,Sou Ryuzaki,Kazumichi Yokota,Yuhui He,Takashi Washio,Kaoru Tamada,Tomoji Kawai, Communications Materials, Springer Science and Business Media LLC, Vol. 2, No. 1, 2021/12
  • Application of an Electrochemical Microflow Reactor for Cyanosilylation: Machine Learning-Assisted Exploration of Suitable Reaction Conditions for Semi-Large-Scale Synthesis, Eisuke Sato,Mayu Fujii,Hiroki Tanaka,Koichi Mitsudo,Masaru Kondo,Shinobu Takizawa,Hiroaki Sasai,Takashi Washio,Kazunori Ishikawa,Seiji Suga, The Journal of Organic Chemistry, American Chemical Society (ACS), Vol. 86, No. 22, p. 16035-16044, 2021/11/19
  • Detecting Single Molecule Deoxyribonucleic Acid in a Cell Using a Three‐Dimensionally Integrated Nanopore, Makusu Tsutsui,Kazumichi Yokota,Akihide Arima,Takashi Washio,Yoshinobu Baba,Tomoji Kawai, Small Methods, Wiley, Vol. 5, No. 9, p. 2100542-2100542, 2021/08/15
  • Analysis on Microstructure–Property Linkages of Filled Rubber Using Machine Learning and Molecular Dynamics Simulations, Takashi Kojima,Takashi Washio,Satoshi Hara,Masataka Koishi,Naoya Amino, Polymers, MDPI AG, Vol. 13, No. 16, p. 2683-2683, 2021/08/11
  • Deep Learning‐Enhanced Nanopore Sensing of Single‐Nanoparticle Translocation Dynamics, Makusu Tsutsui,Takayuki Takaai,Kazumichi Yokota,Tomoji Kawai,Takashi Washio, Small Methods, Wiley, Vol. 5, No. 7, p. 2100191-2100191, 2021/05/14
  • Classification from positive and unlabeled data based on likelihood invariance for measurement, Takeshi Yoshida,Takashi Washio,Takahito Ohshiro,Masateru Taniguchi, Intelligent Data Analysis, IOS Press, Vol. 25, No. 1, p. 57-79, 2021/01/26
  • A Photoswitchable Fluorescent Protein for Hours-Time-Lapse and Sub-Second-Resolved Super-Resolution Imaging., Tetsuichi Wazawa,Ryohei Noma,Shusaku Uto,Kazunori Sugiura,Takashi Washio,Takeharu Nagai, Microscopy (Oxford, England), 2021/01/22
  • Odor Sensor System Using Chemosensitive Resistor Array and Machine Learning, Rui Yatabe,Atsushi Shunori,Bartosz Wyszynski,Yosuke Hanai,Atsuo Nakao,Masaya Nakatani,Akio Oki,Hiroaki Oka,Takashi Washio,Kiyoshi Toko, IEEE Sensors Journal, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, Vol. 21, No. 2, p. 2077-2083, 2021/01/15
  • Solid-State Nanopore Platform Integrated with Machine Learning for Digital Diagnosis of Virus Infection., Akihide Arima,Makusu Tsutsui,Takashi Washio,Yoshinobu Baba,Tomoji Kawai, Analytical chemistry, Vol. 93, No. 1, p. 215-227, 2021/01/12
  • Unsupervised Noise Reduction for Nanochannel Measurement Using Noise2Noise Deep Learning, Takayuki Takaai,Makusu Tsutsui,Takashi Washio, Lecture Notes in Computer Science, Springer International Publishing, p. 44-56, 2021
  • Breaking the curse of dimensionality with Isolation Kernel., Kai Ming Ting,Takashi Washio,Ye Zhu 0002,Yang Xu, CoRR, Vol. abs/2109.14198, 2021
  • Isolation Kernel Density Estimation., Kai Ming Ting,Takashi Washio,Jonathan R. Wells,Hang Zhang, IEEE International Conference on Data Mining(ICDM), IEEE, p. 619-628, 2021
  • Isolation kernel: the X factor in efficient and effective large scale online kernel learning., Kai Ming Ting,Jonathan R. Wells,Takashi Washio, Data Mining and Knowledge Discovery, Vol. 35, No. 6, p. 2282-2312, 2021
  • Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation, Masaru Kondo,Akimasa Sugizaki,Md. Imrul Khalid,H. D. P. Wathsala,Kazunori Ishikawa,Satoshi Hara,Takayuki Takaai,Takashi Washio,Shinobu Takizawa,Hiroaki Sasai, Green Chemistry, Royal Society of Chemistry (RSC), Vol. 23, No. 16, p. 5825-5831, 2021
  • Synthesis of computer simulation and machine learning for achieving the best material properties of filled rubber, Takashi Kojima,Takashi Washio,Satoshi Hara,Masataka Koishi, Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1, 2020/12
  • Machine learning-driven electronic identifications of single pathogenic bacteria, Shota Hattori,Rintaro Sekido,Iat Wai Leong,Makusu Tsutsui,Akihide Arima,Masayoshi Tanaka,Kazumichi Yokota,Takashi Washio,Tomoji Kawai,Mina Okochi, Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1, 2020/12
  • Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap, Yuki Komoto,Takahito Ohshiro,Takeshi Yoshida,Etsuko Tarusawa,Takeshi Yagi,Takashi Washio,Masateru Taniguchi, Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1, 2020/12
  • Digital Pathology Platform for Respiratory Tract Infection Diagnosis via Multiplex Single-Particle Detections., Akihide Arima,Makusu Tsutsui,Takeshi Yoshida,Kenji Tatematsu,Tomoko Yamazaki,Kazumichi Yokota,Shun'ichi Kuroda,Takashi Washio,Yoshinobu Baba,Tomoji Kawai, ACS sensors, Vol. 5, No. 11, p. 3398-3403, 2020/11/25
  • An artificial intelligence nanopore platform for SARS-CoV-2 virus detection, 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,Kazunori Tomono, Research Square, 2020/10/28
  • Nano-corrugated Nanochannels for In Situ Tracking of Single-Nanoparticle Translocation Dynamics, Makusu Tsutsui,Kazumichi Yokota,Yuhui He,Takashi Washio,Tomoji Kawai, ACS Sensors, American Chemical Society (ACS), Vol. 5, No. 8, p. 2530-2536, 2020/08/28
  • Artificial Intelligence Uncovered Clinical Factors for Cardiovascular Events in Myocardial Infarction Patients with Glucose Intolerance., Kazuhiro Shindo,Hiroki Fukuda,Tatsuro Hitsumoto,Yohei Miyashita,Jiyoong Kim,Shin Ito,Takashi Washio,Masafumi Kitakaze, Cardiovascular drugs and therapy, Vol. 34, No. 4, p. 535-545, 2020/08
  • Isolation Distributional Kernel: A New Tool for Point & Group Anomaly Detection., Kai Ming Ting,Bi-Cun Xu,Takashi Washio,Zhi-Hua Zhou, CoRR, Vol. abs/2009.12196, 2020
  • Isolation Distributional Kernel: A New Tool for Kernel based Anomaly Detection., Kai Ming Ting,Bi-Cun Xu,Takashi Washio,Zhi-Hua Zhou, KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD), ACM, p. 198-206, 2020
  • A comparative study of data-dependent approaches without learning in measuring similarities of data objects., Sunil Aryal,Kai Ming Ting,Takashi Washio,Gholamreza Haffari, Data Mining and Knowledge Discovery, Vol. 34, No. 1, p. 124-162, 2020
  • Highly biocompatible super-resolution imaging: Spod-onspan, Tetsuichi Wazawa,Takashi Washio,Takeharu Nagai, Neuromethods, Vol. 154, p. 229-244, 2020
  • Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut-Currier and [3+2] annulation sequence, Masaru Kondo,H. D.P. Wathsala,Makoto Sako,Yutaro Hanatani,Kazunori Ishikawa,Satoshi Hara,Takayuki Takaai,Takashi Washio,Shinobu Takizawa,Hiroaki Sasai, Chemical Communications, Vol. 56, No. 8, p. 1259-1262, 2020
  • Free-hand gas identification based on transfer function ratios without gas flow control, Gaku Imamura,Kota Shiba,Genki Yoshikawa,Takashi Washio, Scientific Reports, Vol. 9, No. 1, 2019/12/01
  • Free-hand gas identification based on transfer function ratios without gas flow control, Gaku Imamura,Kota Shiba,Genki Yoshikawa,Takashi Washio, SCIENTIFIC REPORTS, NATURE PUBLISHING GROUP, Vol. 9, 2019/07
  • Back-Side Polymer-Coated Solid-State Nanopore Sensors, I.W.Leong,M.Tsutsui,T.Nakada,M.Taniguchi,T.Washio,T.Kawai, ACS Omega, AMER CHEMICAL SOC, Vol. 4, No. 7, p. 12561-12566, 2019/07
  • High-Precision Single-Molecule Identification Based on Single-Molecule Information within a Noisy Matrix, M.Taniguchi,T.Ohshiro,Y.Komoto,T.Takaai,T.Yoshida,T.Washio, J.Phys.Chem.C, Vol. 123, No. 25, p. 15867-15873, 2019/06
  • Field-effect transistor array modified by a stationary phase to generate informative signal patterns for machine learning-assisted recognition of gas-phase chemicals, Toshihiro Yoshizumi,Tatsuro Goda,Rui Yatabe,Akio Oki,Akira Matsumoto,Hiroaki Oka,Takashi Washio,Kiyoshi Toko,Yuji Miyahara, Molecular Systems Design and Engineering, Vol. 4, No. 2, p. 386-389, 2019/04
  • Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning., Kai Ming Ting,Jonathan R. Wells,Takashi Washio, CoRR, Vol. abs/1907.01104, 2019
  • A new simple and effective measure for bag-of-word inter-document similarity measurement., Sunil Aryal,Kai Ming Ting,Takashi Washio,Gholamreza Haffari, CoRR, Vol. abs/1902.03402, 2019
  • Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning., Atsushi Shunori,Rui Yatabe,Bartosz Wyszynski,Yosuke Hanai,Atsuo Nakao,Masaya Nakatani,Akio Oki,Hiroaki Oka,Takashi Washio,Kiyoshi Toko, ISOEN, p. 1-3, 2019
  • SPoD-Net: Fast Recovery of Microscopic Images Using Learned ISTA., Satoshi Hara 0001,Weichih Chen,Takashi Washio,Tetsuichi Wazawa,Takeharu Nagai, Proceedings of The 11th Asian Conference on Machine Learning(ACML), PMLR, p. 694-709, 2019
  • Analysis of cause-effect inference by comparing regression errors., Patrick Blöbaum,Dominik Janzing,Takashi Washio,Shohei Shimizu,Bernhard Schölkopf, PeerJ Computer Science, Vol. 5, 2019
  • Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms., Kai Ming Ting,Ye Zhu 0002,Mark J. Carman,Yue Zhu,Takashi Washio,Zhi-Hua Zhou, Machine Learning, Vol. 108, No. 2, p. 331-376, 2019
  • Electric field interference and bimodal particle translocation in nano-integrated multipores, Tsutsui, Makusu,Yokota, Kazumichi,Nakada, Tomoko,Arima, Akihide,Tonomura, Wataru,Taniguchi, Masateru,Washio, Takashi,Kawai, Tomoji, Nanoscale, 2019
  • High-throughput single-particle detections using a dual-height-channel-integrated pore, Tonomura, Wataru,Tsutsui, Makusu,Arima, Akihide,Yokota, Kazumichi,Taniguchi, Masateru,Washio, Takashi,Kawai, Tomoji, Lab on a Chip, Vol. 19, p. 1352-1358, 2019
  • Silicon substrate effects on ionic current blockade in solid-state nanopores, Tsutsui, Makusu,Yokota, Kazumichi,Nakada, Tomoko,Arima, Akihide,Tonomura, Wataru,Taniguchi, Masateru,Washio, Takashi,Kawai, Tomoji, Nanoscale, Vol. 11, p. 4190-4197, 2019
  • Identifying Single Particles in Air Using a 3D-Integrated Solid-State Pore, Tsutsui, Makusu,Yokota, Kazumichi,Yoshida, Takeshi,Hotehama, Chie,Kowada, Hiroe,Esaki, Yuko,Taniguchi, Masateru,Washio, Takashi,Kawai, Tomoji, ACS Sensors, Vol. 4, No. 3, p. 748-755, 2019
  • Identifying multiple viral species at a single particle level using a combination of nanopores and machine leaning approach, Akihide Arima,Makusu Tsutsui,Yoshida Takeshi,Kazumichi Yokota,Wataru Tonomura,Takao Yasui,Taisuke Shimada,Tomoko Yamazaki,Kenji Tatematsu,Shunichi Kuroda,Masateru Taniguchi,Takashi Washio,Tomoji Kawai,Yoshinobu Baba, 23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019, p. 1238-1239, 2019
  • Discriminating drug-resistant bacteria using AI analysis on fine current changes from inner ION leakages, Aomi Yoshikawa,Takao Yasui,Taisuke Shimada,Seiji Yamasaki,Kunihiko Nishino,Takeshi Yanagida,Kazuki Nagashima,Takashi Washio,Tomoji Kawai,Yoshinobu Baba, 23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019, p. 852-853, 2019
  • Identifying Single Viruses Using Biorecognition Solid-State Nanopores., Akihide Arima,Ilva Hanun Harlisa,Takeshi Yoshida,Makusu Tsutsui,Masayoshi Tanaka,Kazumichi Yokota,Wataru Tonomura,Jiro Yasuda,Masateru Taniguchi,Takashi Washio,Mina Okochi,Tomoji Kawai, Journal of the American Chemical Society, Vol. 140, No. 48, p. 16834-16841, 2018/12/05
  • Selective detections of single-viruses using solid-state nanopores., Akihide Arima,Makusu Tsutsui,Ilva Hanun Harlisa,Takeshi Yoshida,Masayoshi Tanaka,Kazumichi Yokota,Wataru Tonomura,Masateru Taniguchi,Mina Okochi,Takashi Washio,Tomoji Kawai, Scientific reports, Vol. 8, No. 1, p. 16305-16305, 2018/11/02
  • Analysis of nanomechanical sensing signals; physical parameter estimation for gas identification, Gaku Imamura,Kota Shiba,Genki Yoshikawa,Takashi Washio, AIP Advances, Vol. 8, No. 7, 2018/07/01
  • Analysis of nanomechanical sensing signals; physical parameter estimation for gas identification, Gaku Imamura,Kota Shiba,Genki Yoshikawa,Takashi Washio, AIP ADVANCES, AMER INST PHYSICS, Vol. 8, No. 7, 2018/07
  • Highly biocompatible super-resolution fluorescence imaging using the fast photoswitching fluorescent protein Kohinoor and SPoD-ExPAN with L-p-regularized image reconstruction, Wazawa Tetsuichi,Arai Yoshiyuki,Kawahara Yoshinobu,Takauchi Hiroki,Washio Takashi,Nagai Takeharu, MICROSCOPY, Vol. 67, No. 2, p. 89-98, 2018/04
  • Identification of Individual Bacterial Cells through the Intermolecular Interactions with Peptide-Functionalized Solid-State Pores., Makusu Tsutsui,Masayoshi Tanaka,Takahiro Marui,Kazumichi Yokota,Takeshi Yoshida,Akihide Arima,Wataru Tonomura,Masateru Taniguchi,Takashi Washio,Mina Okochi,Tomoji Kawai, Analytical chemistry, Vol. 90, No. 3, p. 1511-1515, 2018/02/06
  • Learning Graph Representation via Formal Concept Analysis., Yuka Yoneda,Mahito Sugiyama,Takashi Washio, CoRR, Vol. abs/1812.03395, 2018
  • Analysis of Cause-Effect Inference via Regression Errors., Patrick Blöbaum,Dominik Janzing,Takashi Washio,Shohei Shimizu,Bernhard Schölkopf, CoRR, Vol. abs/1802.06698, 2018
  • A Rare and Critical Condition Search Technique and its Application to Telescope Stray Light Analysis., Keiichi Kisamori,Takashi Washio,Yoshio Kameda,Ryohei Fujimaki, Proceedings of the 2018 SIAM International Conference on Data Mining(SDM), SIAM, p. 567-575, 2018
  • Which Outlier Detector Should I use?, Kai Ming Ting,Sunil Aryal,Takashi Washio, IEEE International Conference on Data Mining(ICDM), IEEE Computer Society, p. 8-8, 2018
  • Cause-Effect Inference by Comparing Regression Errors., Patrick Blöbaum,Dominik Janzing,Takashi Washio,Shohei Shimizu,Bernhard Schölkopf, International Conference on Artificial Intelligence and Statistics(AISTATS), PMLR, p. 900-909, 2018
  • Local contrast as an effective means to robust clustering against varying densities., Bo Chen 0009,Kai Ming Ting,Takashi Washio,Ye Zhu 0002, Machine Learning, Vol. 107, No. 8-10, p. 1621-1645, 2018
  • Temporal Response of Ionic Current Blockade in Solid-State Nanopores, Tsutsui, Makusu,Yokota, Kazumichi,Arima, Akihide,Tonomura, Wataru,Taniguchi, Masateru,Washio, Takashi,Kawai, Tomoji, ACS Applied Materials & Interfaces, Vol. 10, No. 40, p. 34751-34757, 2018
  • Particle Capture in Solid-State Multipores, Tsutsui, Makusu,Yokota, Kazumichi,Nakada, Tomoko,Arima, Akihide,Tonomura, Wataru,Taniguchi, Masateru,Washio, Takashi,Kawai, Tomoji, ACS Sensors, 2018
  • Multimodal resistive pulse analysis using a low-aspect-ratio nanopore, Makusu Tsutsui,Takeshi Yoshida,Masayoshi Tanaka,Kazumichi Yokota,Akihide Arima,Wataru Tonomura,Masateru Taniguchi,Mina Okochi,Takashi Washio,Tomoji Kawai, 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018, Vol. 2, p. 754-757, 2018
  • Discriminating single-bacterial shape using low-aspect-ratio pores., 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,Tomoji Kawai, Scientific reports, Vol. 7, No. 1, p. 17371-17371, 2017/12/12
  • A novel principle for causal inference in data with small error variance., Patrick Blöbaum,Shohei Shimizu,Takashi Washio, 25th European Symposium on Artificial Neural Networks(ESANN), 2017
  • Machine Learning Independent of Population Distributions for Measurement., Takashi Washio,Gaku Imamura,Genki Yoshikawa, 2017 IEEE International Conference on Data Science and Advanced Analytics(DSAA), IEEE, p. 212-221, 2017
  • Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors., Kai Ming Ting,Takashi Washio,Jonathan R. Wells,Sunil Aryal, Machine Learning, Vol. 106, No. 1, p. 55-91, 2017
  • Data-dependent dissimilarity measure: an effective alternative to geometric distance measures., Sunil Aryal,Kai Ming Ting,Takashi Washio,Gholamreza Haffari, Knowledge and Information Systems, Vol. 53, No. 2, p. 479-506, 2017
  • Quantum-state anomaly detection for arbitrary errors using a machine-learning technique, Satoshi Hara,Takafumi Ono,Ryo Okamoto,Takashi Washio,Shigeki Takeuchi, PHYSICAL REVIEW A, AMER PHYSICAL SOC, Vol. 94, No. 4, 2016/10
  • Error Asymmetry in Causal and Anticausal Regression., Patrick Blöbaum,Takashi Washio,Shohei Shimizu, CoRR, Vol. abs/1610.03263, 2016
  • Advances in Knowledge Discovery and Data Mining - 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part II, PAKDD (2), Springer, Vol. 9652, 2016
  • Advances in Knowledge Discovery and Data Mining - 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I, PAKDD, Springer, Vol. 9651, 2016
  • A Novel Continuous and Structural VAR Modeling Approach and Its Application to Reactor Noise Analysis., Marina Demeshko,Takashi Washio,Yoshinobu Kawahara,Yuriy Pepyolyshev, ACM Transactions on Intelligent Systems and Technology, Vol. 7, No. 2, p. 24-22, 2016
  • Data science in Asia (for PAKDD 2016)., James Bailey 0001,Latifur Khan,Takashi Washio, International Journal of Data Science and Analytics, Vol. 2, No. 3-4, p. 93-94, 2016
  • Toxicogenomic prediction with graph-based structured regularization on transcription factor network, Nagata Keisuke,Kawahara Yoshinobu,Washio Takashi,Unami Akira, Fundamental Toxicological Sciences, The Japanese Society of Toxicology, Vol. 3, No. 2, p. 39-46, 2016
  • Particle Trajectory-Dependent Ionic Current Blockade in Low-Aspect-Ratio Pores, Makusu Tsutsui,Yuhui He,Kazumichi Yokota,Akihide Arima,Sadato Hongo,Masateru Taniguchi,Takashi Washio,Tomoji Kawai, ACS NANO, AMER CHEMICAL SOC, Vol. 10, No. 1, p. 803-809, 2016/01
  • Discriminative and generative models in causal and anticausal settings, Patrick Blöbaum,Shohei Shimizu,Takashi Washio, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, Vol. 9505, p. 209-221, 2015
  • Half-space mass: a maximally robust and efficient data depth method., Bo Chen 0009,Kai Ming Ting,Takashi Washio,Gholamreza Haffari, Machine Learning, Vol. 100, No. 2-3, p. 677-699, 2015
  • Toxicogenomic prediction with group sparse regularization based on transcription factor network information, Nagata Keisuke,Kawahara Yoshinobu,Washio Takashi,Unami Akira, Fundamental Toxicological Sciences, The Japanese Society of Toxicology, Vol. 2, No. 4, p. 161-170, 2015
  • Toxicity prediction from toxicogenomic data based on class association rule mining, Keisuke Nagata,Takashi Washio,Yoshinobu Kawahara,Akira Unami, Toxicology Reports, Elsevier Inc., Vol. 1, p. 1133-1142, 2014/12/01
  • Anomaly detection in reconstructed quantum states using a machine-learning technique, Satoshi Hara,Takafumi Ono,Ryo Okamoto,Takashi Washio,Shigeki Takeuchi, PHYSICAL REVIEW A, AMER PHYSICAL SOC, Vol. 89, No. 2, 2014/02
  • Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM., Takanori Inazumi,Takashi Washio,Shohei Shimizu,Joe Suzuki,Akihiro Yamamoto,Yoshinobu Kawahara, CoRR, Vol. abs/1401.5636, 2014
  • Improving iForest with Relative Mass., Sunil Aryal,Kai Ming Ting,Jonathan R. Wells,Takashi Washio, Advances in Knowledge Discovery and Data Mining - 18th Pacific-Asia Conference, Springer, p. 510-521, 2014
  • Mp-Dissimilarity: A Data Dependent Dissimilarity Measure., Sunil Aryal,Kai Ming Ting,Gholamreza Haffari,Takashi Washio, 2014 IEEE International Conference on Data Mining(ICDM), IEEE Computer Society, p. 707-712, 2014
  • LiNearN: A new approach to nearest neighbour density estimator., Jonathan R. Wells,Kai Ming Ting,Takashi Washio, Pattern Recognition, Vol. 47, No. 8, p. 2702-2720, 2014
  • ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders., Tatsuya Tashiro,Shohei Shimizu,Aapo Hyvärinen,Takashi Washio, Neural Computation, Vol. 26, No. 1, p. 57-83, 2014
  • Learning a common substructure of multiple graphical Gaussian models, Satoshi Hara,Takashi Washio, NEURAL NETWORKS, PERGAMON-ELSEVIER SCIENCE LTD, Vol. 38, p. 23-38, 2013/02
  • Density Power Divergence を用いたロバスト能動 回帰学習, 十河康弘,植野剛,河原吉伸,鷲尾隆, 人工知能学会論文誌, Vol. 28, No. 1, p. 13-21, 2013/01
  • ESTIMATION OF CAUSAL STRUCTURES IN LONGITUDINAL DATA USING NON-GAUSSIANITY, Kento Kadowaki,Shohei Shimizu,Takashi Washio, 2013 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), IEEE, 2013
  • Efficiently rewriting large multimedia application execution traces with few event sequences., Christiane Kamdem Kengne,Léon Constantin Fopa,Alexandre Termier,Noha Ibrahim,Marie-Christine Rousset,Takashi Washio,Miguel Santana, The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD), ACM, p. 1348-1356, 2013
  • A Novel Structural AR Modeling Approach for a Continuous Time Linear Markov System., Marina Demeshko,Takashi Washio,Yoshinobu Kawahara, 13th IEEE International Conference on Data Mining Workshops, IEEE Computer Society, p. 104-113, 2013
  • Active learning for noisy oracle via density power divergence., Yasuhiro Sogawa,Tsuyoshi Ueno,Yoshinobu Kawahara,Takashi Washio, Neural Networks, Vol. 46, p. 133-143, 2013
  • DEMass: a new density estimator for big data., Kai Ming Ting,Takashi Washio,Jonathan R. Wells,Fei Tony Liu,Sunil Aryal, Knowledge and Information Systems, Vol. 35, No. 3, p. 493-524, 2013
  • Separation of stationary and non-stationary sources with a generalized eigenvalue problem, Satoshi Hara,Yoshinobu Kawahara,Takashi Washio,Paul von Buenau,Terumasa Tokunaga,Kiyohumi Yumoto, NEURAL NETWORKS, PERGAMON-ELSEVIER SCIENCE LTD, Vol. 33, p. 7-20, 2012/09
  • Efficient Graph Sequence Mining Using Reverse Search, INOKUCHI Akihiro,IKUTA Hiroaki,WASHIO Takashi, IEICE Trans. Inf. & Syst., The Institute of Electronics, Information and Communication Engineers, Vol. 95, No. 7, p. 1947-1958, 2012/07/01
  • FRISSMiner : Mining Frequent Graph Sequence Patterns Induced by Vertices, INOKUCHI Akihiro,WASHIO Takashi, IEICE Trans. Inf. & Syst., The Institute of Electronics, Information and Communication Engineers, Vol. 95, No. 6, p. 1590-1602, 2012/06/01
  • Robust Active Learning for Linear Regression via Density Power Divergence, Yasuhiro Sogawa,Tsuyoshi Ueno,Yoshinobu Kawahara,Takashi Washio, NEURAL INFORMATION PROCESSING, ICONIP 2012, PT III, SPRINGER-VERLAG BERLIN, Vol. 7665, p. 594-602, 2012
  • Bootstrap confidence intervals in DirectLiNGAM, Kittitat Thamvitayakul,Shohei Shimizu,Tsuyoshi Ueno,Takashi Washio,Tatsuya Tashiro, 12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2012), IEEE, p. 659-668, 2012
  • Discovering causal structures in binary exclusive-or skew acyclic models, Takanori Inazumi,Takashi Washio,Shohei Shimizu,Joe Suzuki,Akihiro Yamamoto,Yoshinobu Kawahara, CoRR, AUAI Press, Vol. abs/1202.3736, p. 373-382, 2012
  • Mining Rules for Rewriting States in a Transition-Based Dependency Parser., Akihiro Inokuchi,Ayumu Yamaoka,Takashi Washio,Yuji Matsumoto 0001,Masayuki Asahara,Masakazu Iwatate,Hideto Kazawa, PRICAI 2012: Trends in Artificial Intelligence - 12th Pacific Rim International Conference on Artificial Intelligence(PRICAI), Springer, p. 133-145, 2012
  • Weighted Likelihood Policy Search with Model Selection., Tsuyoshi Ueno,Kohei Hayashi,Takashi Washio,Yoshinobu Kawahara, Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6(NIPS), p. 2366-2374, 2012
  • Estimation of Causal Orders in a Linear Non-Gaussian Acyclic Model: A Method Robust against Latent Confounders., Tatsuya Tashiro,Shohei Shimizu,Aapo Hyvärinen,Takashi Washio, Artificial Neural Networks and Machine Learning - ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Springer, p. 491-498, 2012
  • Special issue on the best papers of SDM'11., Chris Clifton,Takashi Washio, Statistical Analysis and Data Mining, Vol. 5, No. 1, p. 1-2, 2012
  • Fast and Accurate PSD Matrix Estimation by Row Reduction., Hiroshi Kuwajima,Takashi Washio,Ee-Peng Lim, IEICE Transactions on Information & Systems, Vol. 95-D, No. 11, p. 2599-2612, 2012
  • Anomalous Neighborhood Selection, Satoshi Hara,Takashi Washio, 12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2012), IEEE, p. 474-480, 2012
  • Group Sparse Inverse Covariance Selection with a Dual Augmented Lagrangian Method, Satoshi Hara,Takashi Washio, NEURAL INFORMATION PROCESSING, ICONIP 2012, PT III, SPRINGER-VERLAG BERLIN, Vol. 7665, p. 108-115, 2012
  • Estimating exogenous variables in data with more variables than observations, Yasuhiro Sogawa,Shohei Shimizu,Teppei Shimamura,Aapo Hyvarinen,Takashi Washio,Seiya Imoto, NEURAL NETWORKS, PERGAMON-ELSEVIER SCIENCE LTD, Vol. 24, No. 8, p. 875-880, 2011/10
  • Discovering causal structures in binary exclusive-or skew acyclic models., Takanori Inazumi,Takashi Washio,Shohei Shimizu,Joe Suzuki,Akihiro Yamamoto,Yoshinobu Kawahara, UAI 2011, Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, Barcelona, Spain, July 14-17, 2011, AUAI Press, p. 373-382, 2011
  • Analysis of residence time in shopping using RFID Data an application of the Kernel density estimation to RFID - An application of the Kernel density estimation to RFID, Shinya Miyazaki,Takashi Washio,Katsutoshi Yada, Proceedings - IEEE International Conference on Data Mining, ICDM, Vol. pp.1170-1176, p. 1170-1176, 2011
  • Prismatic Algorithm for Discrete D.C. Programming Problems, Yoshinobu Kawahara,Takashi Washio, CoRR, Vol. abs/1108.4217, 2011
  • Density Estimation Based on Mass., Kai Ming Ting,Takashi Washio,Jonathan R. Wells,Fei Tony Liu, 11th IEEE International Conference on Data Mining(ICDM), IEEE Computer Society, p. 715-724, 2011
  • DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model., Shohei Shimizu,Takanori Inazumi,Yasuhiro Sogawa,Aapo Hyvärinen,Yoshinobu Kawahara,Takashi Washio,Patrik O. Hoyer,Kenneth Bollen, Journal of Machine Learning Research, Vol. 12, p. 1225-1248, 2011
  • Analyzing relationships among ARMA processes based on non-Gaussianity of external influences., Yoshinobu Kawahara,Shohei Shimizu,Takashi Washio, Neurocomputing, Vol. 74, No. 12-13, p. 2212-2221, 2011
  • Common Substructure Learning of Multiple Graphical Gaussian Models, Satoshi Hara,Takashi Washio, MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT II, SPRINGER-VERLAG BERLIN, Vol. 6912, p. 1-16, 2011
  • Special section on data mining and statistical science, Masashi Sugiyama,Tomoyuki Higuchi,Tsuyoshi Ide,Akihiro Inokuchi,Toshihiro Kamishima,Hiroyuki Minami,Shinichi Nakajima,Atsuyoshi Nakamura,Koichi Shinoda,Koji Tsuda,Takashi Washio, IEICE Transactions on Information and Systems, Vol. E93-D, No. 10, 2010/10
  • Development of data mining platform MUSASHI towards service computing, Kohei Ichikawa,Katsutoshi Yada,Takashi Washio, Proceedings - 2010 IEEE International Conference on Granular Computing, GrC 2010, IEEE Computer Society, p. 235-240, 2010
  • An experimental comparison of linear non-Gaussian causal discovery methods and their variants, Yasuhiro Sogawa,Shohei Shimizu,Yoshinobu Kawahara,Takashi Washio, 2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010, IEEE, 2010
  • Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models, Takanori Inazumi,Shohei Shimizu,Takashi Washio, LATENT VARIABLE ANALYSIS AND SIGNAL SEPARATION, SPRINGER-VERLAG BERLIN, Vol. 6365, p. 221-228, 2010
  • GroupLiNGAM: Linear non-Gaussian acyclic models for sets of variables, Yoshinobu Kawahara,Kenneth Bollen,Shohei Shimizu,Takashi Washio, CoRR, Vol. abs/1006.5041, 2010
  • Mining Frequent Graph Sequence Patterns Induced by Vertices., Akihiro Inokuchi,Takashi Washio, Proceedings of the SIAM International Conference on Data Mining(SDM), SIAM, p. 466-477, 2010
  • GTRACE2: Improving Performance Using Labeled Union Graphs., Akihiro Inokuchi,Takashi Washio, Advances in Knowledge Discovery and Data Mining, Springer, p. 178-188, 2010
  • Graph Classification Based on Optimizing Graph Spectra., Nguyen Duy Vinh,Akihiro Inokuchi,Takashi Washio, Discovery Science - 13th International Conference, Springer, p. 205-220, 2010
  • Best papers from the 12th Pacific-Asia conference on knowledge discovery and data mining (PAKDD2008)., Takashi Washio,Einoshin Suzuki,Kai Ming Ting, Knowledge and Information Systems, Vol. 25, No. 2, p. 209-210, 2010
  • A new particle filter for high-dimensional state-space models based on intensive and extensive proposal distribution., Viet Phuong Nguyen,Takashi Washio,Tomoyuki Higuchi, International Journal of Knowledge Engineering and Soft Data Paradigms, Vol. 2, No. 4, p. 284-311, 2010
  • Modelling deposit outflow in financial crises: application to branch management and customer relationship management., Katsutoshi Yada,Takashi Washio,Yasuharu Ukai, International Journal of Advanced Intelligence Paradigms, Vol. 2, No. 2/3, p. 254-270, 2010
  • GTRACE: Mining Frequent Subsequences from Graph Sequences., Akihiro Inokuchi,Takashi Washio, IEICE Transactions on Information & Systems, Vol. 93-D, No. 10, p. 2792-2804, 2010
  • Stationary Subspace Analysis as a Generalized Eigenvalue Problem, Satoshi Hara,Yoshinobu Kawahara,Takashi Washio,Paul von Buenau, NEURAL INFORMATION PROCESSING: THEORY AND ALGORITHMS, PT I, SPRINGER-VERLAG BERLIN, Vol. 6443, p. 422-+, 2010
  • New Frontiers in Applied Data Mining, PAKDD 2008 International Workshops, Osaka, Japan, May 20-23, 2008. Revised Selected Papers, PAKDD Workshops, Springer, Vol. 5433, 2009
  • Advances in Machine Learning, First Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2-4, 2009. Proceedings, ACML, Springer, Vol. 5828, 2009
  • Modeling Bank Runs in Financial Crises., Katsutoshi Yada,Takashi Washio,Yasuharu Ukai,Hisao Nagaoka, The Review of Socionetwork Strategies, Vol. 3, No. 1, p. 19-31, 2009
  • Special Issue on Data-Mining and Statistical Science., Takashi Washio, New Generation Computing, Vol. 27, No. 4, p. 281-284, 2009
  • Optimization of Budget Allocation for TV Advertising, Kohei Ichikawa,Katsutoshi Yada,Namiko Nakachi,Takashi Washio, KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT II, PROCEEDINGS, SPRINGER-VERLAG BERLIN, Vol. 5712, p. 270-+, 2009
  • Optimization of budget allocation for TV advertising, Kohei Ichikawa,Katsutoshi Yada,Namiko Nakachi,Takashi Washio, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, Vol. 5712 LNAI, No. PART 2, p. 270-277, 2009
  • Advances in Knowledge Discovery and Data Mining, 12th Pacific-Asia Conference, PAKDD 2008, Osaka, Japan, May 20-23, 2008 Proceedings, PAKDD, Springer, Vol. 5012, 2008
  • A Range Query Approach for High Dimensional Euclidean Space Based on EDM Estimation., Kentarou Kido,Hiroshi Kuwajima,Takashi Washio, Proceedings of the SIAM International Conference on Data Mining(SDM), SIAM, p. 387-398, 2008
  • A Bank Run Model in Financial Crises., Katsutoshi Yada,Takashi Washio,Yasuharu Ukai,Hisao Nagaoka, Knowledge-Based Intelligent Information and Engineering Systems, Springer, p. 703-710, 2008
  • A Fast Method to Mine Frequent Subsequences from Graph Sequence Data., Akihiro Inokuchi,Takashi Washio, Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008)(ICDM), IEEE Computer Society, p. 303-312, 2008
  • DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm., Alexandre Termier,Marie-Christine Rousset,Michèle Sebag,Kouzou Ohara,Takashi Washio,Hiroshi Motoda, IEEE Transactions on Knowledge and Data Engineering, Vol. 20, No. 3, p. 300-320, 2008
  • Modeling dynamic substate chains among massive states., Viet Phuong Nguyen,Takashi Washio, Intelligent Data Analysis, Vol. 12, No. 3, p. 271-291, 2008
  • Analysis on a relation between enterprise profit and financial state by using data mining techniques, Takashi Washio,Yasuo Shinnou,Katsutoshi Yada,Hiroshi Motoda,Takashi Okada, NEW FRONTIERS IN ARTIFICIAL INTELLIGENCE, SPRINGER-VERLAG BERLIN, Vol. 4384, p. 305-316, 2007
  • Communicability Criteria of Law Equations Discovery., Takashi Washio,Hiroshi Motoda, Computational Discovery of Scientific Knowledge, Springer, p. 98-119, 2007
  • A Classification Method Based on Subspace Clustering and Association Rules., Takashi Washio,Koutarou Nakanishi,Hiroshi Motoda, New Generation Computing, Vol. 25, No. 3, p. 235-245, 2007
  • Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction., Phu Chien Nguyen,Kouzou Ohara,Akira Mogi,Hiroshi Motoda,Takashi Washio, Advances in Knowledge Discovery and Data Mining(PAKDD), Springer, p. 390-399, 2006
  • Knowledge Discovery by Complete Search on Discrete Structures, WASHIO Takashi, Journal of The Society of Instrument and Control Engineers, The Society of Instrument and Control Engineers, Vol. 44, No. 5, p. 307-312, 2005/05/10
  • Deriving Class Association Rules Based on Levelwise Subspace Clustering., Takashi Washio,Koutarou Nakanishi,Hiroshi Motoda, Knowledge Discovery in Databases: PKDD 2005, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases(PKDD), Springer, p. 692-700, 2005
  • Cl-GBI: A Novel Approach for Extracting Typical Patterns from Graph-Structured Data., Phu Chien Nguyen,Kouzou Ohara,Hiroshi Motoda,Takashi Washio, Advances in Knowledge Discovery and Data Mining(PAKDD), Springer, p. 639-649, 2005
  • Mutagenicity Risk Analysis by Using Class Association Rules., Takashi Washio,Koutarou Nakanishi,Hiroshi Motoda,Takashi Okada, New Frontiers in Artificial Intelligence, Springer, p. 436-445, 2005
  • Discovering Time Differential Law Equations Containing Hidden State Variables and Chaotic Dynamics., Takashi Washio,Fuminori Adachi,Hiroshi Motoda, IJCAI-05(IJCAI), Professional Book Center, p. 1642-1644, 2005
  • Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering., Takashi Washio,Yuki Mitsunaga,Hiroshi Motoda, Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005)(ICDM), IEEE Computer Society, p. 793-796, 2005
  • Efficient Mining of High Branching Factor Attribute Trees., Alexandre Termier,Marie-Christine Rousset,Michèle Sebag,Kouzou Ohara,Takashi Washio,Hiroshi Motoda, Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005)(ICDM), IEEE Computer Society, p. 785-788, 2005
  • SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos., Takashi Washio,Fuminori Adachi,Hiroshi Motoda, Discovery Science, Springer, p. 253-266, 2005
  • Multi-structure Information Retrieval Method Based on Transformation Invariance., Fuminori Adachi,Takashi Washio,Atsushi Fujimoto,Hiroshi Motoda,Hidemitsu Hanafusa, New Generation Computing, Vol. 23, No. 4, p. 291-313, 2005
  • Enhancing the plausibility of law equation discovery through cross check among multiple scale-type-based models., Takashi Washio,Hiroshi Motoda,Yuji Niwa, Journal of Experimental and Theoretical Artificial Intelligence, Vol. 17, No. 1-2, p. 129-143, 2005
  • A General Framework for Mining Frequent Subgraphs from Labeled Graphs., Akihiro Inokuchi,Takashi Washio,Hiroshi Motoda, Fundamenta Informaticae, Vol. 66, No. 1-2, p. 53-82, 2005
  • Using a Hash-Based Method for Apriori-Based Graph Mining., Phu Chien Nguyen,Takashi Washio,Kouzou Ohara,Hiroshi Motoda, Knowledge Discovery in Databases: PKDD 2004, 8th European Conference on Principles and Practice of Knowledge Discovery in Databases(PKDD), Springer, p. 349-361, 2004
  • Density-based spam detector., Kenichi Yoshida,Fuminori Adachi,Takashi Washio,Hiroshi Motoda,Teruaki Homma,Akihiro Nakashima,Hiromitsu Fujikawa,Katsuyuki Yamazaki, Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD), ACM, p. 486-493, 2004
  • Density-Based Spam Detector., Kenichi Yoshida,Fuminori Adachi,Takashi Washio,Hiroshi Motoda,Teruaki Homma,Akihiro Nakashima,Hiromitsu Fujikawa,Katsuyuki Yamazaki, IEICE Transactions on Information & Systems, Vol. 87-D, No. 12, p. 2678-2688, 2004
  • Adaptive Ripple Down Rules method based on minimum description length principle., Tetsuya Yoshida,Takuya Wada,Hiroshi Motoda,Takashi Washio, Intelligent Data Analysis, Vol. 8, No. 3, p. 239-265, 2004
  • Data Mining and Machine Learning, WASHIO Takashi, Journal of The Society of Instrument and Control Engineers, The Society of Instrument and Control Engineers, Vol. 42, No. 6, p. 480-484, 2003/06/10
  • Classifier Construction by Graph-Based Induction for Graph-Structured Data., Warodom Geamsakul,Takashi Matsuda,Tetsuya Yoshida,Hiroshi Motoda,Takashi Washio, Advances in Knowledge Discovery and Data Mining(PAKDD), Springer, p. 52-62, 2003
  • Performance Evaluation of Decision Tree Graph-Based Induction., Warodom Geamsakul,Takashi Matsuda,Tetsuya Yoshida,Hiroshi Motoda,Takashi Washio, Discovery Science, Springer, p. 128-140, 2003
  • Complete Mining of Frequent Patterns from Graphs: Mining Graph Data., Akihiro Inokuchi,Takashi Washio,Hiroshi Motoda, Machine Learning, Vol. 50, No. 3, p. 321-354, 2003
  • ., WASHIO Takashi, CICSJ Bulletin, Division of Chemical Information and Computer Sciences The Chemical Society of Japan, Vol. 21, No. 2, p. 37-37, 2003
  • Applying data mining to a field quality watchdog task, Satoshi Hori,Hirokazu Taki,Takashi Washio,Hiroshi Motoda, Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi), Vol. 140, No. 2, p. 18-25, 2002/07/30
  • Scientific Law Equation Discovery from Observed Data, WASHIO Takashi, Journal of The Society of Instrument and Control Engineers, The Society of Instrument and Control Engineers, Vol. 41, No. 5, p. 319-324, 2002/05/10
  • Knowledge Discovery from Structured Data by Beam-Wise Graph-Based Induction., Takashi Matsuda,Hiroshi Motoda,Tetsuya Yoshida,Takashi Washio, PRICAI 2002: Trends in Artificial Intelligence(PRICAI), Springer, p. 255-264, 2002
  • Case Generation Method for Constructing an RDR Knowledge Base., Keisei Fujiwara,Tetsuya Yoshida,Hiroshi Motoda,Takashi Washio, PRICAI 2002: Trends in Artificial Intelligence(PRICAI), Springer, p. 228-237, 2002
  • Extension of the RDR Method That Can Adapt to Environmental Changes and Acquire Knowledge from Both Experts and Data., Takuya Wada,Tetsuya Yoshida,Hiroshi Motoda,Takashi Washio, PRICAI 2002: Trends in Artificial Intelligence(PRICAI), Springer, p. 218-227, 2002
  • Adaptive Ripple Down Rules Method based on Minimum Description Length Principle., Tetsuya Yoshida,Hiroshi Motoda,Takashi Washio, Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002)(ICDM), IEEE Computer Society, p. 530-537, 2002
  • Toward the Discovery of First Principle Based Scientific Law Equations., Takashi Washio,Hiroshi Motoda, Progress in Discovery Science, Springer, p. 553-564, 2002
  • Inductive Thermodynamics from Time Series Data Analysis., Hiroshi H. Hasegawa,Takashi Washio,Yukari Ishimiya, Progress in Discovery Science, Springer, p. 384-394, 2002
  • Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction., Takashi Matsuda,Hiroshi Motoda,Tetsuya Yoshida,Takashi Washio, Discovery Science, Springer, p. 422-429, 2002
  • Attribute Generation Based on Association Rules., Masahiro Terabe,Takashi Washio,Hiroshi Motoda,Osamu Katai,Tetsuo Sawaragi, Knowledge and Information Systems, Vol. 4, No. 3, p. 329-349, 2002
  • Graph-based induction and its applications., Takashi Matsuda,Hiroshi Motoda,Takashi Washio, Advanced Engineering Informatics, Vol. 16, No. 2, p. 135-143, 2002
  • Graph-Based Induction for General Graph Structured Data and Its Applications, MATSUDA Takashi,MOTODA Hiroshi,WASHIO Takashi, Transactions of the Japanese Society for Artificial Intelligence, The Japanese Society for Artificial Intelligence, Vol. 16, p. 363-374, 2001/11/01
  • Knowledge Acquisition from Both Human Expert and Data., Takuya Wada,Hiroshi Motoda,Takashi Washio, Knowledge Discovery and Data Mining - PAKDD 2001(PAKDD), Springer, p. 550-561, 2001
  • S3Bagging: Fast Classifier Induction Method with Subsampling and Bagging., Masahiro Terabe,Takashi Washio,Hiroshi Motoda, Advances in Intelligent Data Analysis(IDA), Springer, p. 177-186, 2001
  • Discovering Admissible Simultaneous Equation Models from Observed Data., Takashi Washio,Hiroshi Motoda,Yuji Niwa, Machine Learning: EMCL 2001(ECML), Springer, p. 539-551, 2001
  • A Description Length-Based Decision Criterion for Default Knowledge in the Ripple Down Rules Method., Takuya Wada,Tadashi Horiuchi,Hiroshi Motoda,Takashi Washio, Knowledge and Information Systems, Vol. 3, No. 2, p. 146-167, 2001
  • An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data., Akihiro Inokuchi,Takashi Washio,Hiroshi Motoda, Principles of Data Mining and Knowledge Discovery(PKDD), Springer, p. 13-23, 2000
  • Extension of Graph-Based Induction for General Graph Structured Data., Takashi Matsuda,Tadashi Horiuchi,Hiroshi Motoda,Takashi Washio, Knowledge Discovery and Data Mining, Current Issues and New Applications(PAKDD), Springer, p. 420-431, 2000
  • Enhancing the Plausibility of Law Equation Discovery., Takashi Washio,Hiroshi Motoda,Yuji Niwa, Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000)(ICML), Morgan Kaufmann, p. 1127-1134, 2000
  • Nonequilibrium Thermodynamics from Time Series Data Analysis., Hiroshi H. Hasegawa,Takashi Washio,Yukari Ishimiya,Takeshi Saito, Discovery Science, Springer, p. 304-305, 2000
  • Graph-Based Induction for General Graph Structured Data and Its Application to Chemical Compound Data., Takashi Matsuda,Tadashi Horiuchi,Hiroshi Motoda,Takashi Washio, Discovery Science, Springer, p. 99-111, 2000
  • Basket Analysis for Graph Structured Data., Akihiro Inokuchi,Takashi Washio,Hiroshi Motoda,Kouhei Kumasawa,Naohide Arai, Methodologies for Knowledge Discovery and Data Mining(PAKDD), Springer, p. 420-431, 1999
  • Characterization of Default Knowledge in Ripple Down Rules Method., Takuya Wada,Tadashi Horiuchi,Hiroshi Motoda,Takashi Washio, Methodologies for Knowledge Discovery and Data Mining(PAKDD), Springer, p. 284-295, 1999
  • A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Tree., Masahiro Terabe,Osamu Katai,Tetsuo Sawaragi,Takashi Washio,Hiroshi Motoda, Methodologies for Knowledge Discovery and Data Mining(PAKDD), Springer, p. 143-147, 1999
  • Discovering Admissible Model Equations from Observed Data Based on Scale-Types and Identity Constrains., Takashi Washio,Hiroshi Motoda,Yuji Niwa, Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence(IJCAI), Morgan Kaufmann, p. 772-779, 1999
  • Graph-Based Induction for General Graph Structured Data., Takashi Matsuda,Tadashi Horiuchi,Hiroshi Motoda,Takashi Washio,Kohei Kumazawa,Naohide Arai, Discovery Science, Springer, p. 340-342, 1999
  • Derivation of the Topology Structure from Massive Graph Data., Akihiro Inokuchi,Takashi Washio,Hiroshi Motoda, Discovery Science, Springer, p. 330-332, 1999
  • "Thermodynamics" from Time Series Data Analysis., Hiroshi H. Hasegawa,Takashi Washio,Yukari Ishimiya, Discovery Science, Springer, p. 326-327, 1999
  • Autonomous Recovery Execution in Nuclear Power Plant by the Agent., Yuji Niwa,Masahiro Terabe,Takashi Washio, Cognition, Technology & Work, Vol. 1, No. 4, p. 197-210, 1999
  • Mining Association Rules for Estimation and Prediction., Takashi Washio,Hiroshi Motoda, Research and Development in Knowledge Discovery and Data Mining(PAKDD), Springer, p. 417-419, 1998
  • Development of SDS2: Smart Discovery System for Simultaneous Equation Systems., Takashi Washio,Hiroshi Motoda, Discovery Science, Springer, p. 352-363, 1998
  • Discovering Admissible Simultaneous Equations of Large Scale Systems., Takashi Washio,Hiroshi Motoda, Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference(AAAI/IAAI), AAAI Press / The MIT Press, p. 189-196, 1998
  • Flexible Multiple Semicoarsening for Three-Dimensional Singularly Perturbed Problems., Takashi Washio,Cornelis W. Oosterlee, SIAM Journal on Scientific Computing, Vol. 19, No. 5, p. 1646-1666, 1998
  • Discovery of first-principle equations based on scale-type-based and data-driven reasoning., Takashi Washio,Hiroshi Motoda, Knowledge Based Systems, Vol. 10, No. 7, p. 403-411, 1998
  • Discovering Admissible Models of Complex Systems Based on Scale-Types and Idemtity Constraints., Takashi Washio,Hiroshi Motoda, Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Morgan Kaufmann, p. 810-819, 1997
  • A New Approach to Quantitative and Credible Diagnosis for Multiple Faults of Components and Sensors., Takashi Washio,Masatake Sakuma,Masaharu Kitamura, Artificial Intelligence, Vol. 91, No. 1, p. 103-130, 1997
  • Identification of Unknown Factors in Subjective Evaluation of Interface, WASHIO Takashi,KITAMURA Masaharu, JES Ergonomics, Japan Ergonomics Society, Vol. 37, p. 308-309, 1996/04/10
  • A History-Oriented Envisioning Method., Takashi Washio,Hiroshi Motoda, PRICAI'96: Topics in Artificial Intelligence(PRICAI), Springer, p. 312-323, 1996
  • Application of Fuzzy Integral to Human Reliability, WASHIO Takashi, Journal of Japan Society for Fuzzy Theory and Systems, Japan Society for Fuzzy Theory and Intelligent Informatics, Vol. 5, No. 5, p. 958-969, 1993

Misc.

  • AIと固体ナノポアセンサによるウイルス検査, 有馬彰秀,筒井真楠,鷲尾隆,馬場嘉信,馬場嘉信,馬場嘉信,川合知二, 生物工学会誌, Vol. 101, No. 8, 2023
  • Measurement Informatics and Its Application in Science, Takashi Washio, Proceedings of SciX2022: SciX (The Great SCIentific eXchange) Conference 2022, No. 342, 2022/10
  • Developments of control system for ion source using machine learning, Y Morita,M Fukuda,T Yorita,H Kanda,K Hatanaka,T Saitou,H Tamura,Y Yasuda,T Washio,Y Nakashima,M Iwasaki,H W Koay,K Takeda,T Hara,T H Chong,H Zhao, Journal of Physics: Conference Series, IOP Publishing, Vol. 2244, No. 1, p. 012105-012105, 2022/04/01
  • 3D integrated nanopore for single cell lysis to single-molecule DNA detections, 筒井真楠,横田一道,有馬彰秀,鷲尾隆,馬場嘉信,川合知二, 応用物理学会春季学術講演会講演予稿集(CD-ROM), Vol. 69th, 2022
  • Early detection of brain tumors by using next-gen machinery deep learning algorithm-based urinary liquid biopsy, 夏目敦至,夏目敦至,安井隆雄,安井隆雄,鷲尾隆,北野詳太郎,青木恒介,市川裕樹,水沼未雅,高山和也,高山和也,齋藤竜太,若林俊彦,馬場嘉信,馬場嘉信, 日本脳腫瘍学会学術集会プログラム・抄録集, Vol. 39th, 2021
  • ナノポアデバイスを用いた単一生体粒子分析—応用物理学会 有機分子・バイオエレクトロニクス分科会研究会 ここまで進んだ有機分子・バイオエレクトロニクス研究, 有馬 彰秀,筒井 真楠,吉田 剛,横田 一道,立松 健司,山﨑 智子,黒田 俊一,谷口 正輝,鷲尾 隆,川合 知二,馬場 嘉信, Molecular electronics and bioelectronics = 応用物理学会,有機分子・バイオエレクトロニクス分科会会誌 / 応用物理学会有機分子・バイオエレクトロニクス分科会 編, 応用物理学会有機分子・バイオエレクトロニクス分科会, Vol. 31, No. 2, p. 93-96, 2020
  • ナノポアデバイスを用いた単一生体粒子分析, 有馬彰秀,筒井真楠,吉田剛,横田一道,立松健司,山崎智子,黒田俊一,谷口正輝,鷲尾隆,川合知二,馬場嘉信,馬場嘉信,馬場嘉信, Molecular Electronics and Bioelectronics, Vol. 31, No. 2, 2020
  • 外部摂動イオン電流による薬剤耐性大腸菌の識別, 吉川碧海,安井隆雄,安井隆雄,安井隆雄,嶋田泰介,嶋田泰介,山崎聖司,西野邦彦,柳田剛,長嶋一樹,鷲尾隆,川合知二,馬場嘉信,馬場嘉信,馬場嘉信, 日本化学会春季年会講演予稿集(CD-ROM), Vol. 99th, 2019
  • ナノバイオデバイスと機械学習の融合による多項目ウイルス識別, 有馬彰秀,有馬彰秀,筒井真楠,殿村渉,横田一道,安井隆雄,安井隆雄,嶋田泰佑,嶋田泰佑,山崎智子,立松健司,黒田俊一,谷口正輝,鷲尾隆,川合知二,馬場嘉信,馬場嘉信,馬場嘉信, 化学とマイクロ・ナノシステム学会研究会講演要旨集, Vol. 39th, 2019
  • 機械学習と分子認識ナノポアを用いた1ウイルス識別, 筒井真楠,有馬彰秀,吉田剛,横田一道,殿村渉,谷口正輝,鷲尾隆,川合知二,HARLISA Ilva Hanun,田中祐圭,大河内美奈, 応用物理学会春季学術講演会講演予稿集(CD-ROM), Vol. 66th, 2019
  • ナノポア計測と機械学習によるインフルエンザウイルス識別, 筒井真楠,有馬彰秀,吉田剛,横田一道,殿村渉,谷口正輝,鷲尾隆,川合知二,ILVA Harlisa,田中祐圭,大河内美奈, 日本化学会春季年会講演予稿集(CD-ROM), Vol. 98th, 2018
  • フラジェリン認識ペプチド修飾ポアセンサによる大腸菌の個別計測, 大河内美奈,大河内美奈,田中祐圭,田中祐圭,丸井貴皓,丸井貴皓,筒井真楠,筒井真楠,横田一道,横田一道,鷲尾隆,鷲尾隆,谷口正輝,谷口正輝, 電気化学秋季大会講演要旨集(CD-ROM), Vol. 2018, 2018
  • フラジェリン認識ペプチドを修飾したポアセンサによる微生物の検出, 大河内美奈,大河内美奈,田中祐圭,田中祐圭,丸井貴皓,丸井貴皓,筒井真楠,筒井真楠,横田一道,横田一道,鷲尾隆,鷲尾隆,谷口正輝,谷口正輝,河合知二,河合知二, 化学とマイクロ・ナノシステム学会研究会講演要旨集, Vol. 37th, 2018
  • Image Reconstruction for Super Resolution Microscope Using Recursive Bayesian Computation, KIDO Shunsuke,WASHIO Takashi,WAZAWA Tetsuichi,NAGAI Takeharu, Proceedings of the Annual Conference of JSAI, The Japanese Society for Artificial Intelligence, Vol. 2018, No. 0, p. 3L203-3L203, 2018
  • 低アスペクト比ポアセンサと機械学習法による1粒子形状識別 (M&BE研究会 有機分子・バイオエレクトロニクスの最新動向と応用展開), 筒井 真楠,谷口 正輝,鷲尾 隆,川合 知二, Molecular electronics and bioelectronics = 応用物理学会,有機分子・バイオエレクトロニクス分科会会誌, 応用物理学会有機分子・バイオエレクトロニクス分科会, Vol. 28, No. 2, p. 65-68, 2017/05
  • ナノポアと機械学習による1細菌の識別 : 物理計測と機械学習で分子認識能を創る, 谷口 正輝,鷲尾 隆,川合 知二, 化学 = Chemistry, 化学同人, Vol. 72, No. 2, p. 33-38, 2017/02
  • 微生物結合ペプチドを修飾したポアセンサにおけるイオン電流の応答解析, 服部翔太,イルファ ハヌンハルリサ,丸井貴皓,田中祐圭,大河内美奈,有馬彰秀,筒井真楠,谷口正輝,鷲尾隆,川合知二, 化学工学会年会研究発表講演要旨集(CD-ROM), Vol. 82nd, 2017
  • 微生物判別デバイスの開発に向けたペプチド探索, 服部翔太,服部翔太,田中祐圭,田中祐圭,有馬彰秀,有馬彰秀,筒井真楠,筒井真楠,谷口正輝,谷口正輝,鷲尾隆,鷲尾隆,川合知二,川合知二,大河内美奈,大河内美奈, 化学とマイクロ・ナノシステム学会研究会講演要旨集, Vol. 35th, 2017
  • 遺伝子工学的に開発した蛍光プローブによる細胞生理機能超解像イメージング, 和沢 鉄一,新井 由之,河原 吉伸,中野 雅裕,松田 知己,鷲尾 隆,永井 健治, 人工知能学会全国大会論文集, 一般社団法人 人工知能学会, Vol. 2017, No. 0, p. 2I4OS10b4-2I4OS10b4, 2017
  • Anomaly Detection of Informatical Quantum States by Using Machine Learning, Takashi Washio,The Institute of Scientific and Industrial Research Osaka University, Vol. 30, No. 2, p. 217-223, 2015/03/01
  • Markowitz Portfolio Selection with Change-point Detection and Sparse Estimation, Vol. 29, p. 1-4, 2015
  • Abnormal Event Detection in Crowded Scenes using Structured Sparse Learning, Vol. 28, p. 1-4, 2014
  • Modeling from Big Data, WASHIO Takashi, Systems, control and information, Institute of Systems, Control and Information Engineers, Vol. 58, No. 1, p. 3-8, 2014
  • Quantum state data mining, Ono Takafumi,Okamoto Ryo,Takeuchi Shigeki,Hara Satoshi,Washio Takashi, Meeting abstracts of the Physical Society of Japan, The Physical Society of Japan (JPS), Vol. 68, No. 2, p. 147-147, 2013/08/26
  • Parametric Min-Cuts for Structure Sparse PCA, Vol. 88, p. 109-112, 2013/01/24
  • Principal Component Analysis using Structured Sparsity via Graph Cuts, Vol. 27, p. 1-4, 2013
  • Structure Learning for Anomaly Localization, HARA Satoshi,WASHIO Takashi, The Institute of Electronics, Information and Communication Engineers, Vol. 112, No. 279, p. 17-22, 2012/10/31
  • Weighted Likelihood Policy Search, UENO Tsuyoshi,HAYASHI Kohei,WASHIO Takashi,KAWAHARA Yoshinobu, The Institute of Electronics, Information and Communication Engineers, Vol. 112, No. 279, p. 165-170, 2012/10/31
  • Editor's Introduction to "Discrete Structure Manipulation Systems-The Art of Algorithms for Intelligent Information Processing", WASHIO Takashi,Takashi Washio, Vol. 27, No. 3, p. 231-231, 2012/05/01
  • Recent Development of Intelligent Information Processing with Submodularity(<Special Issue>Discrete Structure Manipulation Systems-The Art of Algorithms for Intelligent Information Processing), KAWAHARA Yoshinobu,NAGANO Kiyohito,WASHIO Takashi,Yoshinobu Kawahara,Kiyohito Nagano,Takashi Washio,The Institute of Scientific and Industrial Research (ISIR) Osaka University:Japan Science and Technology Agency (JST),Institute of Industrial Science The University of Tokyo,The Institute of Scientific and Industrial Research (ISIR) Osaka University:Japan Science and Technology Agency (JST), Vol. 27, No. 3, p. 252-260, 2012/05/01
  • A feature selection method based on randomized algorithm, Vol. 26, p. 1-4, 2012
  • Path Integral Control on Manifold, Vol. 26, p. 1-4, 2012
  • Sparse Inverse Covariance Selection via DAL-ADMM, Vol. 26, p. 1-4, 2012
  • Prismatic Algorithm for Discrete D.C. Programming Problem, KAWAHARA Yoshinobu,WASHIO Takashi, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011(NIPS), The Institute of Electronics, Information and Communication Engineers, Vol. 111, No. 275, p. 93-98, 2011/11/09
  • A Method for Estimating Binary Data Generating Process, INAZUMI Takanori,WASHIO Takashi,SHIMIZU Shohei,SUZUKI Joe,YAMAMOTO Akihiro,KAWAHARA Yoshinobu, The Institute of Electronics, Information and Communication Engineers, Vol. 111, No. 275, p. 155-162, 2011/11/09
  • Learning a Graphical Structure with Clusters, HARA Satoshi,WASHIO Takashi, The Institute of Electronics, Information and Communication Engineers, Vol. 111, No. 275, p. 19-24, 2011/11/09
  • Mining High Dimensional Data in the Info-plosion Era, WASHIO Takashi, The Journal of the Institute of Electronics, Information and Communication Engineers, The Institute of Electronics, Information and Communication Engineers, Vol. 94, No. 8, p. 679-683, 2011/08/01
  • Learning an Invariant Substructure of Multiple Graphical Gaussian Models, HARA Satoshi,WASHIO Takashi, IEICE technical report, The Institute of Electronics, Information and Communication Engineers, Vol. 110, No. 476, p. 177-181, 2011/03/21
  • ANALYZING RELATIONSHIPS BETWEEN CTARMA AND ARMA MODELS, Vol. 25, p. 1-4, 2011
  • Simultaneous Learning of Graphical Structures, Vol. 25, p. 1-4, 2011
  • Analyzing Optimal Marketing Strategies Over Customers' Networks, Vol. 25, p. 1-4, 2011
  • Relational Data Mining on Causal Relations Between Variables, WASHIO Takashi, The Institute of Electronics, Information and Communication Engineers, Vol. 110, No. 76, p. 5-5, 2010/06/07
  • Issues of statistical large scale causal inference and its challenge based on non-Gaussianity, Vol. 75, p. 33-36, 2009/11/13
  • Preface: Featured section on data-mining and statistical science, Tomoyuki Higuchi,Takashi Washio, ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, SPRINGER HEIDELBERG, Vol. 60, No. 4, p. 697-698, 2008/12
  • Research Strategy to Present Your Papers in Prestigious International Conferences(<Special Issue>Writing Good Research Papers for International Conferences), WASHIO Takashi,Takashi Washio,The Institute for Scientific and Industrial Research Osaka University, Journal of Japanese Society for Artificial Intelligence, Vol. 23, No. 3, p. 362-366, 2008/05/01
  • Modeling Dynamics of Massive Dimensional Systems, NGUYEN Viet Phuong,WASHIO Takashi, Vol. 70, p. 239-240, 2008/03/13
  • Data Intensive Computing : No.1 Discrete Structure Mining(<Lecture Series>Intelligent Computing and Related Issues (1)), WASHIO Takashi,Takashi Washio,The Institute of Scientific and Industrial Research (ISIR) Osaka University., Journal of Japanese Society for Artificial Intelligence, Vol. 22, No. 2, p. 263-271, 2007/03/01
  • Editor's Introduction to "Data Mining and Statistical Science"(<Special Issue>Data Mining and Statistical Science), WASHIO Takashi,Takashi Washio,The Institute of Scientific and Industrial Research (ISIR) Osaka University., Vol. 22, No. 2, p. 272-272, 2007/03/01
  • 知識発見から知識体系発見へ(<特集>編集委員2007年の抱負), 鷲尾 隆,Takashi Washio, 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence, Vol. 22, No. 1, p. 22-22, 2007/01/01
  • DryadeによるGene Network DAGデータからの飽和頻出木マイニング, ターミエ アレックサンドル,鷲尾 隆,樋口 知之,玉田 嘉紀,井元 清哉,大原 剛三,元田 浩, 人工知能学会全国大会論文集, 一般社団法人 人工知能学会, Vol. 6, No. 0, p. 7-7, 2006
  • Basics and Present of Graph-based Data Mining, WASHIO Takashi, IPSJ Magazine, Information Processing Society of Japan (IPSJ), Vol. 46, No. 1, p. 20-26, 2005/01/15
  • (1)Deta Mining Applications : Overview and Prospect(Commentary Series : The Voice of Practitioners in Data Mining), WASHIO Takashi,Takashi Washio,The Institute of Scientific and Industrial Research Osaka University, Journal of Japanese Society for Artificial Intelligence, Vol. 19, No. 3, p. 373-375, 2004/05/01
  • Trend of Data Mining Research and Issues in Application to Pattern Recognition : Let's Work Hard Together, WASHIO Takashi, Technical report of IEICE. PRMU, The Institute of Electronics, Information and Communication Engineers, Vol. 103, No. 295, p. 115-120, 2003/09/08
  • A Proposal on Modelling and Its Application of Complex and Social Systems by Scale Constraints, NIWA Yuji,WASHIO Takashi,MOTODA Hiroshi, Correspondences on Human Interface, Human Interface Society, Vol. vol.4,No.2,pp.1-8, No. 2, p. 1-8, 2002
  • Data Mining Contests:Present and Future of Data Mining in Businesss, WASHIO Takashi, IPSJ Magazine, Information Processing Society of Japan (IPSJ), Vol. 42, No. 5, p. 467-471, 2001/05/15
  • Mathematical Models in Law Equation Discovery(Special Issue : "Mathematical Models in Artificial Intelligence toward 21st Century"), WASHIO Takashi,Takashi Washio,Institute of Scientific and Industrial Research Osaka University, Journal of Japanese Society for Artificial Intelligence, Vol. 16, No. 2, p. 245-248, 2001/03/01
  • A proposal of design reasoning model that takes notice of design knowledge (the Third Report) : A proposal of a synthesis language for describing design operational knowledge, YOSHIOKA Masaharu,Takeda Hideaki,WASHIO Takashi,TOMIYAMA Tetsuo, The Proceedings of Design & Systems Conference, The Japan Society of Mechanical Engineers, Vol. 2001, No. 0, p. 281-284, 2001
  • A proposal of design reasoning mode that takes notice of design knowledge (the Forth report) : Implementation of a reasoning model in design and its verification, Nomaguchi Yutaka,Tsumaya Akira,Yoshioka Masaharu,Washio Takashi,Takeda Hideaki,Murakami Tamotsu,Tomiyama Tetsuo, The Proceedings of Design & Systems Conference, The Japan Society of Mechanical Engineers, Vol. 2001, No. 0, p. 285-288, 2001
  • Mathematical Models in Law Equation Discovery, WASHIO Takashi, Vol. 14, p. 32-33, 2000/07/03
  • History and Perspective of Mining Techniques for Structured Data, WASHIO Takashi, Vol. 14, p. 93-96, 2000/07/03
  • Derivation of Exogenously-Driven Causality Based on Physical Laws, Takashi Washio,Nuclear Reactor Laboratory Massachusetts Institute of Technology, Vol. 5, No. 4, p. 482-491, 1990/07/01