Takehisa Yairi
Takehisa Yairi
確認したメール アドレス: g.ecc.u-tokyo.ac.jp
Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion
N Yokoya, T Yairi, A Iwasaki
IEEE Transactions on Geoscience and Remote Sensing 50 (2), 528-537, 2011
Anomaly detection using autoencoders with nonlinear dimensionality reduction
M Sakurada, T Yairi
Proceedings of the MLSDA 2014 2nd Workshop on Machine Learning for Sensory …, 2014
A review on the application of deep learning in system health management
S Khan, T Yairi
Mechanical Systems and Signal Processing 107, 241-265, 2018
An approach to spacecraft anomaly detection problem using kernel feature space
R Fujimaki, T Yairi, K Machida
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005
Fault detection by mining association rules from house-keeping data
T Yairi, Y Kato, K Hori
Proc. of International Symposium on Artificial Intelligence, Robotics and …, 2001
Change-point detection in time-series data based on subspace identification
Y Kawahara, T Yairi, K Machida
Seventh IEEE International Conference on Data Mining (ICDM 2007), 559-564, 2007
Learning Koopman invariant subspaces for dynamic mode decomposition
N Takeishi, Y Kawahara, T Yairi
Advances in Neural Information Processing Systems, 1130-1140, 2017
Telemetry-mining: a machine learning approach to anomaly detection and fault diagnosis for space systems
T Yairi, Y Kawahara, R Fujimaki, Y Sato, K Machida
2nd IEEE International Conference on Space Mission Challenges for …, 2006
An anomaly detection method for spacecraft using relevance vector learning
R Fujimaki, T Yairi, K Machida
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 785-790, 2005
A data-driven health monitoring method for satellite housekeeping data based on probabilistic clustering and dimensionality reduction
T Yairi, N Takeishi, T Oda, Y Nakajima, N Nishimura, N Takata
IEEE Transactions on Aerospace and Electronic Systems 53 (3), 1384-1401, 2017
Bayesian Dynamic Mode Decomposition.
N Takeishi, Y Kawahara, Y Tabei, T Yairi
IJCAI, 2814-2821, 2017
Structured denoising autoencoder for fault detection and analysis
T Tagawa, Y Tadokoro, T Yairi
Asian Conference on Machine Learning, 96-111, 2015
Recent developments in aerial robotics: A survey and prototypes overview
CF Liew, D DeLatte, N Takeishi, T Yairi
arXiv preprint arXiv:1711.10085, 2017
Subspace dynamic mode decomposition for stochastic Koopman analysis
N Takeishi, Y Kawahara, T Yairi
Physical Review E 96 (3), 033310, 2017
Hyperspectral, multispectral, and panchromatic data fusion based on coupled non-negative matrix factorization
N Yokoya, T Yairi, A Iwasaki
2011 3rd workshop on hyperspectral image and signal processing: Evolution in …, 2011
Map building without localization by dimensionality reduction techniques
T Yairi
Proceedings of the 24th international conference on Machine learning, 1071-1078, 2007
A kernel subspace method by stochastic realization for learning nonlinear dynamical systems
Y Kawahara, T Yairi, K Machida
Advances in neural information processing systems, 665-672, 2007
Adaptive limit checking for spacecraft telemetry data using regression tree learning
T Yairi, M Nakatsugawa, K Hori, S Nakasuka, K Machida, N Ishihama
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat …, 2004
Quadrotor or blimp? Noise and appearance considerations in designing social aerial robot
CF Liew, T Yairi
2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2013
Anomaly detection from multivariate time-series with sparse representation
N Takeishi, T Yairi
2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2014
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