- DBLP’s publication list for a nicely formatted summary of my computer science papers.
- Google Scholar Page for the number of citations.
- KDnuggets article on the ranking of data mining conferences.
Conference proceedings (refereed)
- “Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis,”
- “Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes,”
- “Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution,”
- Tsuyoshi Idé, Naoki Abe
- In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023, August 6-10, 2023, Long Beach, California, USA), pp.845-856 [GitHub, slides, poster, 2min intro video]
- “Direction aware positional and structural encoding for directed graph neural networks,”
- “Directed Graph Auto-Encoders,”
- “Cardinality-Regularized Hawkes-Granger Model,”
- Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan, Naoki Abe,
- Advances in Neural Information Processing Systems 34 (NeurIPS 21, Dec 6-14, 2021, virtual), pp.2682-2694 [GitHub, slides, poster, arXiv].
- “Decentralized Collaborative Learning with Probabilistic Data Protection,”
- Tsuyoshi Idé, Rudy Raymond,
- In Proceedings of the 2021 IEEE International Conference on Smart Data Services (SMDS 21, September 5-10, 2021, virtual), pp.234-243 [slides, arXiv, IEEE Xplore].
- “Anomaly Attribution with Likelihood Compensation,”
- Tsuyoshi Idé, Amit Dhurandhar, Jiri Navratil, Moninder Singh, Naoki Abe,
- In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 21, February 2-9, 2021, virtual), pp.4131-4138 [GitHub, slides, poster, official version, arXiv, IBM product].
- “Predicting Nocturnal Hypoglycemia under Free-Living Conditions from Continuous Glucose Monitoring Data with Extended Prediction Horizon,”
- Long Vu, Sarah Kefayati, Tsuyoshi Idé, Venkata Pavuluri, Gretchen Jackson, Lisa Latts, Yuxiang Zhong, Pratik Agrawal, Yuan-chi Chang,
- In AMIA Annual Symposium Proceedings (AIMA 19, November 16-20, Washington D.C., USA), pp.874-882 [PubMed].
- “Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks,”
- “l0–Regularized Sparsity for Probabilistic Mixture Models,”
- “Tensorial Change Analysis using Probabilistic Tensor Regression,”
- “Collaborative Anomaly Detection on Blockchain from Noisy Sensor Data,”
- Tsuyoshi Idé,
- In Proceedings of 2018 IEEE International Conference on Data Mining Workshops (ICDMW); Workshop on Blockchain Systems for Decentralized Mining (BSDM, November 17, Singapore), pp.120-127 [slides, IEEE Xplore].
- “Multi-task Multi-modal Models for Collective Anomaly Detection,”
- Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam,
- Proceedings of the 2017 IEEE International Conference on Data Mining (ICDM 17, November 18-21, 2017, New Orleans, USA), pp.177-186 [slides].
- “A Novel l0-constrained Gaussian Graphical Model for Anomaly Localization,”
- Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg,
- Proceedings of the 17th International Conference on Data Mining Workshops (ICDMW 2017, November 18, 2017, New Orleans, USA), pp.830-833 [slides]
- “Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection,”
- “Unsupervised Object Counting without Object Recognition,”
- Takayuki Katsuki, Tetsuro Morimura, Tsuyoshi Idé,
- Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 16, December 4-8, 2016, Cancun, Mexico), pp.3616-3621 [slides].
- “Change Detection using Directional Statistics (with corrections),”
- “Informative Prediction based on Ordinal Questionnaire Data,” [selected as a Best of ICDM]
- “Latent Trait Analysis for Risk Management of Complex Information Technology Projects,”
- “Probablistic Text Analytics Framework for information Technology Service Desk Tickets,”
- Kuan-Yu Chen, Ee-Ea Jan, Tsuyoshi Idé,
- Proceedings of the 14th IFIP/IEEE International Symposium on Integrated Network Management (IM 2015, May 11-15, 2015, Ottawa, Canada), pp.870-873.
- “A Probabilistic Concept Annotation for IT Service Desk Tickets,”
- Ea-Ee Jan, Kuan-Yu Chen, Tsuyoshi Idé,
- Proceedings of the 7th International Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 14, November 7, 2014, Shanghai, China), pp.21-23 [ACM Digital Library].
- “Probabilistic Two-Level Anomaly Detection for Correlated Systems,”
- Bin Tong, Tetsuro Morimura, Einoshin Suzuki, Tsuyoshi Idé,
- Proceedings of the 21st European Conference on Artificial Intelligence (ECAI 2014, August 18-22, 2014, Prague, Czech), pp.1109-1110 (supplemental material) [IOS Press].
- “Mining for Gold: How to Predict Service Contract Performance with Optimal Accuracy based on Ordinal Risk Assessment Data,”
- Sinem Guven, Mathias Steiner, Tsuyoshi Idé, Sergey Makogon, Alejandro Venegas,
- Proceedings of the 11th IEEE International Conference on Services Computing (IEEE SCC 2014, June 27-July 2, 2014, Anchorage, USA), pp.315-322 [slides].
- “Solving inverse problem of Markov chain with partial observations,”
- Tetsuro Morimura, Takayuki Osogami, and Tsuyoshi Idé,
- Proceedings of Neural Information and Processing Systems (NIPS 2013, December 5-10, 2013, Lake Tahoe, USA), pp.1655-1663.
- “Monitoring Entire-City Traffic using Low-Resolution Web Cameras,”
- Tsuyoshi Idé, Takayuki Katsuki, Tetsuro Morimura, and Robert Morris,
- Proceedings of ITS World Congress Tokyo 2013 (October 14-18, 2013, Tokyo, Japan), #3143 [slides].
- “Identifying the optimal road closure with simulation,”
- Takayuki Osogami, Hideyuki Mizuta, and Tsuyoshi Idé,
- Proceedings of ITS World Congress Tokyo 2013 (October 14-18, 2013, Tokyo, Japan), #3178.
- “Predicting Battery Life from Usage Trajectory Patterns,”
- Toshiro Takahashi, Tsuyoshi Idé,
- Proceedings of International Conference on Pattern Recognition (ICPR 2012, November 11-15, 2012, Tsukuba, Japan), pp.2946-2949.
- “X10-based massive parallel large-scale traffic flow simulation,”
- “Nonlinear Optimization to Generate Non-overlapping Random Dot Patterns,”
- “Trajectory Regression on Road Networks,”
- “Proximity-Based Anomaly Detection using Sparse Structure Learning,”
- “Travel-Time Prediction using Gaussian Process Regression: A Trajectory-Based Approach,”
- “Semi-Supervised Local Fisher Discriminant Analysis for Dimensionality Reduction,”
- Masashi Sugiyama, Tsuyoshi Idé, Shinichi Nakajima, and Jun Sese,
- Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008, May 20-23, 2008, Osaka, Japan); Lecture Notes in Computer Science, Springer, Vol. 5012, 2008, pp.333-344 [link].
- “Unsupervised Change Analysis using Supervised Learning,”
- Shohei Hido, Tsuyoshi Idé, Hisashi Kashima, Harunobu Kubo, and Hirofumi Matsuzawa,
- Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008, May 20-23, 2008, Osaka, Japan); Lecture Notes in Computer Science, Springer, Vol. 5012, 2008, pp.148-159 [link].
- “Computing Correlation Anomaly Scores using Stochastic Nearest Neighbors,”
- Tsuyoshi Idé, Spiros Papadimitriou, and Michail Vlachos,
- Proceedings of the Seventh IEEE International Conference on Data Mining (ICDM 07, October 28-31, 2007, Omaha, USA), pp.523-528 [slides].
- “Change-point detection using Krylov subspace learning,”
- “Translational symmetry in subsequence time-series clustering,”
- Tsuyoshi Idé,
- New Frontiers in Artificial Intelligence: Proceeding of the 20th Annual Conferences of the Japanese Society for Artificial Intelligence (JSAI 2006, June 7-9, 2006, Tokyo), Lecture Notes in Artificial Intelligence, Springer, Vol. 4384, pp.5-18 [final version].
- “Why does Subsequence Time-Series Clustering Produce Sine Waves?,”
- Tsuyoshi Idé,
- Proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 06, September 18-22, 2006, Berlin, Germany), Lecture Notes in Artificial Intelligence, Springer, Vol.4213, pp.311-322 [final version, slides].
- “Pairwise Symmetry Decomposition Method for Generalized Covariance Analysis,”
- “Knowledge Discovery from Heterogeneous Dynamic Systems using Change-Point Correlations,”
- “Network-based Problem Detection for Distributed Systems,”
- H. Kashima, T. Tsumura, T.Idé, T. Nogayama, R. Hirade, H. Etoh, and T. Fukuda,
- Proceedings of the 21st International Conference on Data Engineering (ICDE 2005, April 5-8, 2005, Tokyo, Japan), pp.978-989.
- “Eigenspace-based Anomaly Detection in Computer Systems,”
- “Effective Dimension in Anomaly Detection: Its Application to Computer Systems,”
- Tsuyoshi Idé and Hisashi Kashima,
- Post-proceedings of the Eighteenth Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2004, June 2-4, 2004, Kanazawa, Japan), Lecture Notes in Computer Science, Springer, Vol. 3609, pp.189-204 [final version].
- “Moire-Free Collimating Light Guide with Low-Discrepancy Dot Patterns,”
- Tsuyoshi Idé, H. Numata, H. Mizuta, Y. Taira, M. Suzuki, M. Noguchi, and Y. Katsu,
- Digest of Technical Papers (Society for Information Display 2002, May 19-24, 2002, Boston, USA), pp. 1232-1235 [slides].
Journal (refereed)
- “Sequential Uncertainty Quantification with Contextual Tensors for Social Targeting,”
- Tsuyoshi Idé, Keerthiram Murugesan, Djallel Bouneffouf, Naoki Abe,
- Knowledge and Information Systems, to appear, 2025 [link].
- “Identifying Primary Aldosteronism Patients who Require Adrenal Venous Sampling: A Multi-center Study,”
- Takumi Kitamoto*, Tsuyoshi Idé*, Yuta Tezuka, Norio Wada, Yui Shibayama, Yuya Tsurutani, Tomoko Takiguchi, Kosuke Inoue, Sachiko Suematsu, Kei Omata, Yoshikiyo Ono, Ryo Morimoto, Yuto Yamazaki, Jun Saito, Hironobu Sasano, Fumitoshi Satoh, and Tetsuo Nishikawa (* equal contribution),
- Scientific Reports, Vol. 13 (2023) 21722 [link, GitHub].
- “Diagnostic Spatio-temporal Transformer with Faithful Encoding,”
- Jokin Labaien, Tsuyoshi Idé, Pin-Yu Chen, Ekhi Zugasti, Xabier De Carlos,
- Knowledge-Based Systems, Vol. 274 (2023)110639 [link].
- “Signal and noise extraction from analog memory elements for neuromorphic computing,”
- N. Gong, T. Idé, S. Kim, I. Boybat, A. Sebastian, V. Narayanan, T. Ando,
- Nature Communications, Vol. 9, No. 2102 (2018).
- “City-Wide Traffic Flow Estimation from Limited Number of Low Quality Cameras,”
- Tsuyoshi Idé, T. Katsuki, T. Morimura, and R. Morris,
- IEEE Transactions on Intelligent Transportation Systems, Vol. 18, No. 4, pp.950-959 (2017) [link].
- “Supervised Item Response Models for Informative Prediction,”
- Tsuyoshi Idé and Amit Dhurandhar,
- Knowledge and Information Systems, Vol.51, No.1, pp.235–257, 2017 [link].
- “Toward simulating entire cities with behavioral models of traffic,”
- T. Osogami, T. Imamichi, H. Mizuta, and Tsuyoshi Idé,
- IBM Journal of Research and Development, Vol.57, Issue 5, pp.6:1-6:10, 2013 [link].
- Tetsuro Morimura, Yusuke Tanizawa, Shinya yamasaki, Tsuyoshi Idé,
- Transactions of Society of Automotive Engineers of Japan, Vol.43, No.2, pp.573-578, 2012.
- “Modeling Patent Quality: A System for Large-scale Patentability Analysis using Text Mining,”
- Shohei Hido,Shoko Suzuki, Risa Nishiyama, Takashi Imamichi, Rikiya Takahashi, Tetsuya Nasukawa, Tsuyoshi Idé, Yusuke Kanehira, Rinju Yohda, Takeshi Ueno, Akira Tajima, and Toshiya Watanabe,
- Journal of Information Processing, Vol. 20, No.3, pp.667-671 [link]
- “Trajectory Regression for Travel-Time Prediction,”
- Tsuyoshi Idé, and Sei Kato,
- Transactions of the Japanese Society for Artificial Intelligence, Vol. 25 (2010) , No. 3, pp.377-382 [link].
- “Unsupervised Change Analysis using Supervised Learning,”
- Hirofumi Matsuzawa, Shohei Hido, Tsuyoshi Idé, and Hisashi Kashima,
- IEICE Transactions on on Information and Systems, Vol.E93-D, No.6 pp.816-825, 2010 [link].
- “Semi-supervised local Fisher discriminant analysis for dimensionality reduction,”
- Masashi Sugiyama, Tsuyoshi Idé, Shinichi Nakajima, and Jun Sese,
- Machine Learning Journal, vol.78, no.1-2, pp.35-61, 2010 [link].
- “Recent Advances and Trends in Large-scale Kernel Methods,”
- Hisashi Kashima, Tsuyoshi Idé, Tsuyoshi Kato, and Masashi Sugiyama,
- IEICE Transactions on on Information and Systems, Vol.E92-D, No.7, pp.1338-1353, 2009 [link].
- “Network-Based Problem Detection for Distributed Systems,”
- Hisashi Kashima, Tadashi Tsumura, Tsuyoshi Idé, Takahide Nogayama, Ryo Hirade, Hiroaki Etoh, and Takeshi Fukuda,
- IEICE Transactions on Information and Systems, Vol. J89-D, No.2, pp.183-198, 2006 [link].
- “A novel dot-pattern generation to improve luminance uniformity of an LCD backlight,”
- Tsuyoshi Idé, H. Numata, Y. Taira, H. Mizuta, M. Suzuki, M. Noguchi, and Y. Katsu,
- Journal of the Society for Information Display, Vol.11, No.4 (2003) 659-665 [slides of the original paper].
- “Dot pattern generation technique using molecular dynamics,”
- Tsuyoshi Idé, H. Mizuta, H. Numata, Y. Taira, M. Suzuki, M. Noguchi, and Y. Katsu,
- Journal of the Optical Society of America, A, 20 (2003) 242-255 [link].
- “Nonlocal screening effect in Cu 4p(sigma) -1s resonant X-ray emission spectra of Nd2CuO4,”
- Tsuyoshi Idé and Akio Kotani,
- Journal of the Physical Society of Japan 69 (2000) 3107-3114 [link].
- “Interplay between Raman and fluorescence-like components in resonant X-ray emission spectra of degenerate d0and d1 systems,”
- Tsuyoshi Idé and Akio Kotani,
- Journal of the Physical Society of Japan 69 (2000) 1895-1906 [link].
- “Polarization and momentum dependence of a charge-transfer excitation in Nd2CuO4,”
- K. Hamalainen, J. P. Hill, S. Huotari, C. -C. Kao, L. E. Berman, A. Kotani, Tsuyoshi Idé, J. L. Peng, and R. L. Greene,
- Physical Review B 61 (2000) 1836-1840 [link].
- “Local and nonlocal excitations in Cu 4p-1s resonant X-ray emission spectra of Nd2CuO4,”
- Tsuyoshi Idé and Akio Kotani,
- Journal of the Physical Society of Japan 68 (1999) 3100-3109 [link].
- “A model study on cluster size effects of resonant X-ray emission spectra,”
- Tsuyoshi Idé and Akio Kotani,
- Journal of the Physical Society of Japan 67 (1998) 3621-3629 [link].
- “Theoretical study on cluster size effects on X-ray absorption and resonant X-ray emission spectra in d and f electron systems,”
- A. Kotani and Tsuyoshi Idé,
- Journal of Synchrotron Radiation 6 (1999) 308-309, presented at XAFS X (International Union of Crystallography, Chicago, USA, 10-14 August 1998).
Book
Books
- Tsuyoshi Idé, Introduction to Anomaly Detection using Machine Learning ─ A Practical Guide with R, Corona Publishing, 2015 (in Japanese).
- Tsuyoshi Idé and Masashi Sugiyama, Anomaly Detection and Change Detection, Kodansha Scientific, 2015 (in Japanese).
- Kenji Yamanishi, Ryohei Hisano, Keishi Shimada, Tsubasa Minematsu, Tsuyoshi Idé, “From Anomaly Detection to Risk Management,” Saiensu-sha, 2022 (in Japanese).
Book chapters
- Tsuyoshi Idé, Making relationships simple — A story of graphical lasso, Iwanami Data Science, Vo.5 (2016) pp.48-63 [pdf] (in Japanese).
- Tsuyoshi Idé, Formalizing expert knowledge through machine learning. In S. K. Kwan, J. C. Spohrer, and Y. Sawatani, ed., Global Perspectives on Service Science: Japan, pp.157-175, Springer, 2016 [pdf].
- Tsuyoshi Idé, Change detection from heterogeneous data sources. In Katsutoshi Yada, ed., Data Mining for Service. Springer Verlag, pp.221-243, 2014 [pdf].
Book editors
- Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng (ed.), Advances in Knowledge Discovery and Data Mining (Proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023), Part I, II, III, IV.
- Hattori, T. Kawamura, Tsuyoshi Idé, M. Yokoo, and Y. Murakami, editors. New Frontiers in Artificial Intelligence: JSAI 2008 Conference and Workshops, Revised Selected Papers, volume 5447 of Lecture Notes in Artificial Intelligence. Springer Verlag, 2009.
Book translations
- H. Fujisawa, Tsuyoshi Idé, Computer Age Statistical Inference. Kyoritsu, 2020 (Japanese translation of the book of the same title by Bradley Efron and Trevor Hastie, Cambridge University Press, 2016).
- M. Sugiyama, Tsuyoshi Idé, T. Kamishima, T. Kurita, and E. Maeda
The Elements of Statistical Learning, Kyoritsu, 2014 (Japanese translation of the book of the same title by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie, Springer, 2001). - Tsuyoshi Idé. Chap. 12, Continuous Latent Variables. In H. Motoda, T. Kurita, T. Higuchi, Y. Matsumoto, and N. Murata, ed., Pattern Recognition and Machine Learning. Maruzen, 2012 (Japanese translation of the book of the same title by Christopher Bishop, Springer, 2006).
Invited Talks
- “Explaining What Went Wrong: The Black-Box Anomaly Attribution Problem,”
- IEOR Seminar, Department of Industrial Engineering and Operations Research, Columbia University (November 15, 2024) [slides].
- “Computing Input Responsibility Scores in Black-Box Anomaly Detection,”
- Computer Science Department Colloquium, Rochester Institute of Technology (Oct. 8, 2024) [slides]
- “Decentralized Collaborative Machine Learning Framework with Democracy, Diversity, and Privacy,”
- 2023 International workshop Blockchain Kaigi (BCK 23; Kobe, Japan, Oct. 2023) [slides]
- “Attributing anomalies from black-box predictions,”
- “Explaining Anomalies of Black-Box Regression Function,”
- Trustworthy AI Summit, Taipei Computer Association (January 13, 2023, Taipei, Taiwan) [slides].
- “Artificial Intelligence Seen from Behind the Scenes — A Personal View“,
- Keynote, Research Exhibition 2022, Tokai Pathways to Global Excellence (November 2022, Nagoya University, Japan) [link].
- “Basics and recent developments of anomaly detection: With a focus on causal discovery from event sequences (異常検知についての最近の話題: イベント系列からの因果発見問題を中心に),”
- “Current landscape of artificial intelligence and a few recent topics (AIブームの現在と最近の研究から),”
- Adachi Lab Seminar, Keio University (April 5, 2022), Tokyo (virtual), Japan. [blog article]
- “Machine learning now: A view from America (米国から見た機械学習の今), ”
- “What’s going on in artificial intelligence research: A perspective from America (アメリカから見た人工知能研究の現在),”
- Guest lecture, University of Tokyo (Course ID 4850-1026: Advanced Topics in Frontier Artificial Intelligence II, December 21, 2021) [link]
- “Anomaly detection and statistical machine learning: Foundations and recent advancements,”
- SPS Seminar Series (University of the Western Cape, November 03, 2021) [slides].
- “Anomaly detection: Foundations and recent advancements,”
- JAXA Seminar, Japan Aerospace Exploration Agency (October 22, 2021)
- “Decentralized Collaborative Learning with Probabilistic Data Protection,”
- “Recent advances in machine learning from industrial sensor data,”
- The 12th ICME International Conference on Complex Medical Engineering (CME 2018, September 6-8, 2018), Shimane, Japan [link, slides].
- “Recent advances in sensor data analytics,”
- Department Seminar, Department of Computer Science (January 10, 2018), University at Albany, State University of New York, Albany, USA [slides].
- “Towards cognitive manufacturing,”
- “Towards consumable analytics: Challenges and recent advances,”
- “Formalizing expert knowledge through machine learning,”
- Big Data in Service (March 12, 2014), New York, USA.
- “Formalizing expert knowledge through machine learning,”
- Service Science Research Forum (May 10, 2012), Tokyo, Japan [follow-up book, slides].
- “Historical Perspectives towards Analytics Revolution,”
- The 56th Annual Symposium of the Institute of Systems, Control and Information Engineers (SCI 12, May 21-23, 2012), Kyoto, Japan [link (in Japanese)].
- “Trajectory regression on networks,”
- Japanese-French Frontiers of Science Symposium (JFFoS, January 19-22, 2012), Nice, France [slides].
- “Machine Learning for Anomaly Detection and Risk Analysis, II,”
- IBISML Tutorial (January 12, 2012), Tokyo, Japan.
- “Solving real business problems with math sciences,”
- SIG Service Science, The Operating Research Society of Japan (December 19, 2011), Tsukuba, Japan.
- “Anomaly detection using sparse structure learning,”
- Adachi Lab Seminar, Keio University (December 12, 2010), Tokyo, Japan.
- “On recent advances in machine learning for system identification,”
- DoE Conference 2010 (November 15, 2010), Tokyo, Japan.
- “On the trajectory regression problem on networks,”
- Sugiyama Lab. Seminar, Department of Computer Science, Tokyo Institute of Technology (October 7, 2010), Tokyo, Japan.
- “On a regression problem for path cost,”
- ERATO Seminar, Hokkaido University (September 27, 2010), Sapporo, Japan.
- “Detecting Anomalies from Latent Graph Structures,”
- The 1st Workshop on Latent Dynamics (LD-1, Jun 16, 2010), Tokyo, Japan.
- “On the problem of cost estimation for paths,”
- Mathematical Informatics Colloquium, University of Tokyo (February 24, 2010), Tokyo, Japan.
- “Applying Machine Learning Techniques to Sensor Data Analysis,”
- Global COE `CompView’ Kickoff Event, Tokyo Institute of Technology (December 13, 2007), Tokyo, Japan.
- “Why does subsequence time-series clustering produce sine waves?,”
- Departmental Colloquium, Max Planck Institute for Biological Cybernetics (September 13, 2006), Tübingen, Germany.
- “A Spectral Approach to Anomaly Detection in Computer Systems,”
- Scientific Computing Seminar, Berkeley Lab (April 25, 2005), Berkeley, USA.
- “Feature Extraction and Anomaly Detection in Web-based Computer Systems,”
- The Seventh Workshop on Information-Based Induction Sciences (IBIS2004, November 8 -10, 2004), Tokyo, Japan.
Other presentations
- “Applications of Graphical Gaussian Models for Process Control,”
- Robert J. Baseman, Dzung T. Phan, Dhavalkumar C. Patel, Fateh A. Tipu, Jayant R. Kalagnanam, Tsuyoshi Idé,
- In Proceedings of the Advanced Process Control Conference (APC 2019, October 28-31, 2019, Texas, USA).
Granted patents (as of May 2023)
- Diagnosing Anomalies Detected By Black-box Machine Learning Models, October 31, 2022 – United States of America, 11487650
- Learning Sparsity-constrained Gaussian Graphical Models In Anomaly Detection, January 3, 2022 – United States of America, 11216743
- Incorporating Change Diagnosis Using Probabilistic Tensor Regression Model For Improving Processing Of Materials, August 24, 2020 – United States of America, 10754310
- Managing Anomaly Detection Models For Fleets Of Industrial Equipment, August 3, 2020 – United States of America, 10733813
- Diagnostic Fault Detection Using Multivariate Statistical Pattern Library, April 6, 2020 – United States of America, 10612999
- Change Detection Using Directional Statistics, August 12, 2019 – United States of America, 10378997
- Anomaly Detection Method, Program, And System, November 19, 2018 – United States of America, 10133703
- Method For Cost Estimation Along Arbitrary Paths Using Weight Propagation, January 3, 2018 – Germany, 112010004005
- Anomaly Detection Method, Program, And System, November 20, 2017 – United States of America,
9824069 - Anomaly Detection Method, Program, And System, October 30, 2017 – United States of America,
9805002 - System, Method, And Program For Predicting State Of Battery, March 1, 2017 – China, ZL201210392219.1
- Anomaly Detection Method, Program, And System, November 14, 2016 – United States of America,
9495330 - %mirai-hc% Diagnosis Method For Medical Event Sequences, August 16, 2016 – China, ZL201280060060.1
- Analysis Device, Analysis Method, And Program For Crash Simulation, August 11, 2016 – Japan,
5984142 - Information Processing Apparatus, Calculation Method, Program, And Storage Medium, May 30, 2016 – United States of America, 9354381
- Information Processing Apparatus, Calculation Method, Program, And Storage Medium, May 2, 2016 – United States of America, 9329329
- Calculating Risk Assessment Value Of Event Sequence, April 18, 2016 – United States of America,
9317804 - System, Method, And Program For Predicting State Of Battery, December 10, 2015 – Japan,
5852399 - %mirai-hc% Method, Apparatus And Computer Program For Calculating Risk Assessment Value Of Event Sequence, November 20, 2015 – Japan, 5839970
- Information Processing Apparatus, Calculation Method, Program, And Storage Medium, September 3, 2015 – Japan, 5802041
- Method For Cost Estimation Along Arbitrary Paths Using Weight Propagation, June 24, 2015 – China
ZL201080057419.0 - %mirai-hc% Diagnosis Method For Medical Event Sequences, February 12, 2015 – Japan, 5695763
- Generation Of Uniformly Distributed Dot Patterns, December 17, 2014 – China, ZL201210107397.5
- Method For Cost Estimation Along Arbitrary Paths Using Weight Propagation, November 21, 2014 – Japan, 5651129
- Fault Detection Method For Trains, July 11, 2014 – Japan, 5576567
- Kernel Regression System, Method, And Program, July 3, 2014 – Japan, 5570008
- Cost Evaluation And Prediction, March 24, 2014 – United States of America, 8682633
- Cost Evaluation And Prediction, December 3, 2013 – United States of America, 8600721
- Kernel Regression System, Method, And Program, November 25, 2013 – United States of America, 8595155
- Change Analysis, April 8, 2013 – United States of America, 8417648
- Location Estimation System, Method And Program, March 25, 2013 – United States of America, 8405551
- Location Estimation System, Method And Program, February 22, 2013 – Japan, 5203670
- Travel Time Prediction Using Gaussian Process Regression, February 15, 2013 – Japan, 5198994
- Proximity-based Anomaly Detection Using Sparse Structure Learning, January 25, 2013 – Japan, 5186322
- Method For Cost Estimation Along Arbitrary Paths Using Weight Propagation, January 16, 2013 – United Kingdom, 2487701
- Change Analysis System, Method And Program, December 20, 2012 – Japan, 5159368
- Technique For Detecting Anomaly In Observation Target, March 23, 2012 – Japan, 4953239
- Location Estimation System, Method And Program, March 20, 2012 – United States of America, 8138974
- Online Outlier Detector For Directional Data, December 24, 2010 – Japan, 4652741
- Method And System For Detecting Difference Between Plural Observed Results, December 7, 2010 – United States of America, 7849124
- Diagnostic Data Detection And Control, May 18, 2010 – United States of America, 7720640
- Pairwise Symmetry Decomposition Method For Generalized Covariance Analysis, April 20, 2010 – United States of America, 7702714
- Anomaly Detection, January 11, 2010 – United States of America, 7647524
- Scoring Method For Correlation Anomalies, May 4, 2009 – United States of America, 7529991
- Computer Operation Analysis, February 17, 2009 – United States of America, 7493361
- Methods Involving Computing Correlation Anomaly Scores, January 27, 2009 – United States of America, 7483934
- Malfunction Condition Judgment Apparatus, Control Method, Automobile And Program, January 5, 2009 – United States of America, 7475052
- System And Method For Detecting Difference Between Plural Observed Results, October 17, 2008 – Japan, 4201027
- Method And Apparatus For Discovering Causal Relation From A Large Amount Of Various Time Series Data, September 12, 2008 – Japan, 4183185
- Method And Apparatus For Filtering And Analyzing Signals From Automoblies, August 15, 2008 – Japan, 4170315
- Anomaly Detection Based On Directional Data, July 29, 2008 – United States of America, 7406653
- System And Method Of Evaluating Correlation, July 4, 2008 – Japan, 4148524
- Anomaly Detection, March 18, 2008 – United States of America, 7346803
- A Method Of Problem Determination For Computer Systems, March 14, 2008 – Japan, 4093483
- Method And Apparatus For Anomaly Detection Of Multi-vertex Systems With Dynamic Correlation, March 2, 2007 – Japan, 3922375
- Diagnostic Data Detection And Control, February 20, 2007 – United States of America, 7181365
- Discrete Pattern, Apparatus, Method, And Program Storage Device For Generating And Implementing The Discrete Pattern, March 8, 2005 – United States of America, 6865325
- Liquid Crystal Display Devices With Low-discrepancy Patterns And A Method For Generating Low-discrepancy Patterns, December 1, 2004 – Taiwan, I224698
- Discrete Pattern, June 22, 2004 – United States of America, 6754419