Yoshinobu Kawahara

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	All	Since 2016
Citations	1940	1320
h-index	21	17
i10-index	38	28

420

210

105

315

200820092010201120122013201420152016201720182019202020218 10 46 55 83 114 141 136 172 164 243 314 420 6

Co-authors

Shohei SHIMIZUShiga University & RIKENVerified email at biwako.shiga-u.ac.jp
Keisuke FujiiNagoya UniversityVerified email at i.nagoya-u.ac.jp
Aapo HyvarinenUniversity of HelsinkiVerified email at helsinki.fi
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Chloé-Agathe AzencottMines ParisTechVerified email at mines-paristech.fr
Kenneth BollenDepartment of Psychology and Neuroscience, Department of Sociology, University of North Carolina atVerified email at unc.edu
Karsten BorgwardtProfessor, ETH ZurichVerified email at bsse.ethz.ch
SATOSHI MORINAGANEC CorporationVerified email at nec.com
Dominik G. GrimmProfessor of Bioinformatics at TUM Campus Straubing, HSWTVerified email at hswt.de
Bo XinMicrosoft Research AsiaVerified email at microsoft.com
Wen Gao（高文）Professor of Computer Science, Peking UniversityVerified email at pku.edu.cn
Patrik HoyerAlumni, Aalto University and University of HelsinkiVerified email at alumni.aalto.fi
Masahiro IkedaRIKEN AIP centerVerified email at keio.jp
Mahito SugiyamaAssociate Professor, National Institute of InformaticsVerified email at nii.ac.jp
Satoshi HaraAssistant Professor, Osaka UniversityVerified email at ar.sanken.osaka-u.ac.jp
Paul von Bünauidalab GmbHVerified email at idalab.de
Takayuki ItohOchanomizu UniversityVerified email at is.ocha.ac.jp
Jeffrey A. BilmesProfessor of Electrical Engineering and Computer Science, University of Washington SeattleVerified email at uw.edu
Koh TakeuchiResearcher of NTT Communication Science Labs.Verified email at lab.ntt.co.jp
Tomoharu IwataNTTVerified email at hco.ntt.co.jp

Yoshinobu Kawahara

Professor, IMI, Kyushu University / Team Leader, AIP Center, RIKEN

Verified email at imi.kyushu-u.ac.jp - Homepage

Machine Learning Nonlinear Dynamics Artificial Intelligence Data Science


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Sequential change‐point detection based on direct density‐ratio estimation Y Kawahara, M Sugiyama Statistical Analysis and Data Mining: The ASA Data Science Journal 5 (2 …, 2012	356*	2012
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	219	2011
Learning Koopman invariant subspaces for dynamic mode decomposition N Takeishi, Y Kawahara, T Yairi Advances in Neural Information Processing Systems 30, 1130-1140, 2017	124	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	114	2007
Efficient Generalized Fused Lasso and its Application to the Diagnosis of Alzheimer's Disease. B Xin, Y Kawahara, Y Wang, W Gao Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence …, 2014	77	2014
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	69	2013
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	65	2006
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 (1), 21-49, 2013	56	2013
Dynamic mode decomposition with reproducing kernels for Koopman spectral analysis Y Kawahara Advances in Neural Information Processing Systems 29, 911-919, 2016	51	2016
Minimum average cost clustering K Nagano, Y Kawahara, S Iwata Advances in Neural Information Processing Systems 23, 1759-1767, 2010	47	2010
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	46	2011
Bayesian Dynamic Mode Decomposition N Takeishi, Y Kawahara, Y Tabei, T Yairi The Twenty-Sixth International Joint Conference on Artificial Intelligence …, 2017	40	2017
Subspace dynamic mode decomposition for stochastic Koopman analysis N Takeishi, Y Kawahara, T Yairi Physical Review E 96, 033310, 2017	38	2017
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	38	2012
Submodularity cuts and applications Y Kawahara, K Nagano, K Tsuda, JA Bilmes Advances in Neural Information Processing Systems 22, 916-924, 2009	33	2009
Representative selection with structured sparsity H Wang, Y Kawahara, C Weng, J Yuan Pattern Recognition 63, 268-278, 2017	29	2017
A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model S Shimizu, A Hyvärinen, Y Kawahara, T Washio Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial …, 2009	25*	2009
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	23	2007
Submodular fractional programming for balanced clustering Y Kawahara, K Nagano, Y Okamoto Pattern Recognition Letters 32 (2), 235-243, 2011	22	2011
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), 60, 2016	21	2016

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