| DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model S Shimizu, T Inazumi, Y Sogawa, A Hyvärinen, Y Kawahara, T Washio, ... Journal of Machine Learning Research 12 (Apr), 1225-1248, 2011 | 644 | 2011 |
| Change-point detection in time-series data by direct density-ratio estimation Y Kawahara, M Sugiyama Proceedings of the 2009 SIAM international conference on data mining, 389-400, 2009 | 521 | 2009 |
| Learning Koopman invariant subspaces for dynamic mode decomposition N Takeishi, Y Kawahara, T Yairi Advances in Neural Information Processing Systems 30, 1130-1140, 2017 | 448 | 2017 |
| Change-point detection in time-series data based on subspace identification Y Kawahara, T Yairi, K Machida Proceedings of the Seventh IEEE International Conference on Data Mining …, 2007 | 179 | 2007 |
| Dynamic mode decomposition with reproducing kernels for Koopman spectral analysis Y Kawahara Advances in Neural Information Processing Systems 29, 911-919, 2016 | 116 | 2016 |
| 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 Space Mission Challenges for Information Technology, 2006. SMC-IT 2006 …, 2006 | 114 | 2006 |
| Efficient generalized fused lasso and its application to the diagnosis of Alzheimer’s disease B Xin, Y Kawahara, Y Wang, W Gao Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014 | 108 | 2014 |
| Subspace dynamic mode decomposition for stochastic Koopman analysis N Takeishi, Y Kawahara, T Yairi Physical Review E 96, 033310, 2017 | 90 | 2017 |
| Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios A Takeda, M Niranjan, J Gotoh, Y Kawahara Computational Management Science 10, 21-49, 2013 | 90 | 2013 |
| Efficient network-guided multi-locus association mapping with graph cuts CA Azencott, D Grimm, M Sugiyama, Y Kawahara, KM Borgwardt Bioinformatics 29 (13), i171-i179, 2013 | 81 | 2013 |
| Bayesian Dynamic Mode Decomposition N Takeishi, Y Kawahara, Y Tabei, T Yairi The Twenty-Sixth International Joint Conference on Artificial Intelligence …, 2017 | 75 | 2017 |
| Size-constrained submodular minimization through minimum norm base K Nagano, Y Kawahara, K Aihara Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011 | 71 | 2011 |
| Separation of stationary and non-stationary sources with a generalized eigenvalue problem S Hara, Y Kawahara, T Washio, P Von BüNau, T Tokunaga, K Yumoto Neural networks 33, 7-20, 2012 | 70 | 2012 |
| Representative selection with structured sparsity H Wang, Y Kawahara, C Weng, J Yuan Pattern Recognition 63, 268-278, 2017 | 60 | 2017 |
| Minimum average cost clustering K Nagano, Y Kawahara, S Iwata Advances in Neural Information Processing Systems 23, 1759-1767, 2010 | 52 | 2010 |
| Submodularity cuts and applications Y Kawahara, K Nagano, K Tsuda, JA Bilmes Advances in Neural Information Processing Systems 22, 2009 | 45 | 2009 |
| Koopman spectral kernels for comparing complex dynamics: Application to multiagent sport plays K Fujii, Y Inaba, Y Kawahara Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 41 | 2017 |
| Dynamic mode decomposition in vector-valued reproducing kernel Hilbert spaces for extracting dynamical structure among observables K Fujii, Y Kawahara Neural Networks 117, 94-103, 2019 | 36 | 2019 |
| Efficient generalized fused lasso and its applications B Xin, Y Kawahara, Y Wang, L Hu, W Gao ACM Transactions on Intelligent Systems and Technology (TIST) 7 (4), 1-22, 2016 | 36 | 2016 |
| Analyzing relationships among ARMA processes based on non-Gaussianity of external influences Y Kawahara, S Shimizu, T Washio Neurocomputing 74 (12-13), 2212-2221, 2011 | 36 | 2011 |
Takehisa YAIRIThe University of Tokyo, Research Center for Advanced Science and Technology確認したメール アドレス: g.ecc.u-tokyo.ac.jp
