Koji Tsuda

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Citations	15414	6062
h-index	51	34
i10-index	137	100

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & MPIIVerified email at tu-berlin.de
Kiyoshi AsaiProfessor of Computational Biology, University of TokyoVerified email at k.u-tokyo.ac.jp
Jean-Philippe VertGoogle Brain / Mines ParisTechVerified email at mines-paristech.fr
Hisashi KashimaProfessor, Kyoto UniversityVerified email at i.kyoto-u.ac.jp
Sebastian MikacomtravoVerified email at comtravo.com
Takeaki UnoNational Institute of Informatics, JapanVerified email at nii.jp
Ichigaku TakigawaRIKEN / Hokkaido UniversityVerified email at riken.jp
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Junichiro ShiomiThe University of TokyoVerified email at photon.t.u-tokyo.ac.jp
Yasuo TabeiUnit leader at RIKEN-AIPVerified email at riken.go.jp
Akihiro InokuchiProfessor, Kwansei Gakuin UniversityVerified email at kwansei.ac.jp
Sebastian NowozinPartner Research Manager, Machine Intelligence, Microsoft Research (Cambridge, UK)Verified email at microsoft.com
Tsuyoshi Kato群馬大学Verified email at cs.gunma-u.ac.jp
Yoshihiro YamanishiKyushu Institute of TechnologyVerified email at bio.kyutech.ac.jp
Kana ShimizuWaseda University, National Institute of Advanced Industrial Science and TechnologyVerified email at waseda.jp
Takeuchi IchiroProfessor, Nagoya UniversityVerified email at mae.nagoya-u.ac.jp
Jun SeseHumanome Lab Inc.Verified email at humanome.jp
Isao TanakaKyoto UniversityVerified email at kyoto-u.ac.jp

Koji Tsuda

Professor, GSFS, The University of Tokyo

Verified email at k.u-tokyo.ac.jp - Homepage

Machine Learning Computational Biology


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MIKA S RATSCH G, et al. An introduction to kernel-based learning algorithms KR Muller Neural Network IEEE Transaction 12 (2), 180-201, 2001	4674*	2001
Marginalized kernels between labeled graphs H Kashima, K Tsuda, A Inokuchi Proceedings of the 20th international conference on machine learning (ICML …, 2003	1052	2003
Kernel methods in computational biology B Schölkopf, K Tsuda, JP Vert MIT press, 2004	927	2004
A primer on kernel methods JP Vert, K Tsuda, B Schölkopf Kernel methods in computational biology 47, 35-70, 2004	467	2004
Prediction of low-thermal-conductivity compounds with first-principles anharmonic lattice-dynamics calculations and Bayesian optimization A Seko, A Togo, H Hayashi, K Tsuda, L Chaput, I Tanaka Physical review letters 115 (20), 205901, 2015	361	2015
Bayesian inference and optimal design in the sparse linear model M Seeger, F Steinke, K Tsuda Artificial Intelligence and Statistics, 444-451, 2007	360	2007
Fast protein classification with multiple networks K Tsuda, H Shin, B Schölkopf Bioinformatics 21 (suppl_2), ii59-ii65, 2005	267	2005
Marginalized kernels for biological sequences K Tsuda, T Kin, K Asai Bioinformatics 18 (suppl_1), S268-S275, 2002	255	2002
Discriminative subsequence mining for action classification S Nowozin, G Bakir, K Tsuda 2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007	253	2007
Designing nanostructures for phonon transport via Bayesian optimization S Ju, T Shiga, L Feng, Z Hou, K Tsuda, J Shiomi Physical Review X 7 (2), 021024, 2017	235	2017
Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single-and binary-component solids A Seko, T Maekawa, K Tsuda, I Tanaka Physical Review B 89 (5), 054303, 2014	227	2014
Matrix exponentiated gradient updates for on-line learning and Bregman projection K Tsuda, G Rätsch, MK Warmuth Journal of Machine Learning Research 6 (Jun), 995-1018, 2005	225	2005
COMBO: An efficient Bayesian optimization library for materials science T Ueno, TD Rhone, Z Hou, T Mizoguchi, K Tsuda Materials discovery 4, 18-21, 2016	211	2016
A new discriminative kernel from probabilistic models K Tsuda, M Kawanabe, G Rätsch, S Sonnenburg, KR Müller Advances in Neural Information Processing Systems 14, 2001	204	2001
Link propagation: A fast semi-supervised learning algorithm for link prediction H Kashima, T Kato, Y Yamanishi, M Sugiyama, K Tsuda Proceedings of the 2009 SIAM international conference on data mining, 1100-1111, 2009	176	2009
ChemTS: an efficient python library for de novo molecular generation X Yang, J Zhang, K Yoshizoe, K Terayama, K Tsuda Science and technology of advanced materials 18 (1), 972-976, 2017	173	2017
Kernels for graphs H Kashima, K Tsuda, A Inokuchi Kernel methods in computational biology, 155-170, 2004	168	2004
gBoost: a mathematical programming approach to graph classification and regression H Saigo, S Nowozin, T Kadowaki, T Kudo, K Tsuda Machine Learning 75 (1), 69-89, 2009	148	2009
Learning kernels from biological networks by maximizing entropy K Tsuda, WS Noble Bioinformatics 20 (suppl_1), i326-i333, 2004	142	2004
Weighted substructure mining for image analysis S Nowozin, K Tsuda, T Uno, T Kudo, G BakIr 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007	128	2007

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