| Eigenspace-based anomaly detection in computer systems T Idé, H Kashima Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004 | 284 | 2004 |
| Semi-supervised local Fisher discriminant analysis for dimensionality reduction M Sugiyama, T Idé, S Nakajima, J Sese Machine learning 78 (1-2), 35, 2010 | 280 | 2010 |
| Knowledge discovery from heterogeneous dynamic systems using change-point correlations T Idé, K Inoue Proceedings of 2005 SIAM International Conference on Data Mining (SDM 05 …, 2005 | 101 | 2005 |
| Computing correlation anomaly scores using stochastic nearest neighbors T Idé, S Papadimitriou, M Vlachos Seventh IEEE international conference on data mining (ICDM 2007), 523-528, 2007 | 89 | 2007 |
| Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach. T Idé, S Kato Proceedings of 2009 SIAM International Conference on Data Mining (SDM 09 …, 2009 | 77 | 2009 |
| Unsupervised change analysis using supervised learning S Hido, T Idé, H Kashima, H Kubo, H Matsuzawa Pacific-Asia Conference on Knowledge Discovery and Data Mining, 148-159, 2008 | 67 | 2008 |
| Proximity-Based Anomaly Detection Using Sparse Structure Learning. T Idé, AC Lozano, N Abe, Y Liu Proceedings of 2009 SIAM International Conference on Data Mining (SDM 09 …, 2009 | 65 | 2009 |
| Anomaly detection T Ide, K Yoda, H Kashima, H Etoh, R Hirade US Patent 7,346,803, 2008 | 62 | 2008 |
| Dot pattern generation technique using molecular dynamics T Idé, M Suzuki, M Noguchi, H Mizuta, H Numata, Y Katsu, Y Taira Journal of the Optical Society of America, A 20 (2), 248-255, 2003 | 61 | 2003 |
| Polarization and momentum dependence of a charge-transfer excitation in K Hämäläinen, JP Hill, S Huotari, CC Kao, LE Berman, A Kotani, T Idé, ... Physical Review B 61 (3), 1836, 2000 | 58 | 2000 |
| Discrete pattern T Ide, H Mizuta, Y Taira, A Nishikai US Patent 6,754,419, 2004 | 55 | 2004 |
| Trajectory Regression on Road Networks. T Idé, M Sugiyama Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence …, 2011 | 53 | 2011 |
| Change-point detection using krylov subspace learning T Idé, K Tsuda SIAM International Conference on Data Mining (SDM 2007), 515-520, 2007 | 53 | 2007 |
| Signal and noise extraction from analog memory elements for neuromorphic computing N Gong, T Idé, K S., B I., S A., N V., T Ando Nature Communications 9 (1), 2102, 2018 | 48 | 2018 |
| Discrete pattern, apparatus, method, and program storage device for generating and implementing the discrete pattern T Ide, H Mizuta, Y Taira, A Nishikai US Patent 6,865,325, 2005 | 45 | 2005 |
| Semi-supervised local fisher discriminant analysis for dimensionality reduction M Sugiyama, T Idé, S Nakajima, J Sese Pacific-Asia Conference on Knowledge Discovery and Data Mining, 333-344, 2008 | 38 | 2008 |
| Why does subsequence time-series clustering produce sine waves? T Idé European Conference on Principles of Data Mining and Knowledge Discovery …, 2006 | 37 | 2006 |
| IBM Mega Traffic Simulator T Osogami, T Imamichi, H Mizuta, T Morimura, R Raymond, T Suzumura, ... IBM Res., Tokyo, Japan, IBM Res. Rep. RT0896, 2012 | 34 | 2012 |
| Diagnostic data detection and control K Inoue, T Ide US Patent 7,181,365, 2007 | 34 | 2007 |
| Anomaly detection based on directional data T Ide, K Inoue, T Yamane, H Takeuchi US Patent 8,640,015, 2014 | 33 | 2014 |
Hisashi KashimaProfessor, Kyoto UniversityVerified email at i.kyoto-u.ac.jp
