Koji Tsuda - Google Scholar

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	All	Since 2015
Citations	12291	4899
h-index	43	30
i10-index	110	79

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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 MüllerGoogle Brain (on leave of Professor for Machine Learning, TU Berlin & Korea University, Seoul)Verified 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
Yasuo TabeiUnit leader, RIKEN Center for Advanced Intelligence Project (AIP)Verified email at riken.go.jp
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Akihiro InokuchiProfessor, Kwansei Gakuin UniversityVerified email at kwansei.ac.jp
Ichigaku TakigawaRIKEN / Hokkaido UniversityVerified email at icredd.hokudai.ac.jp
Sebastian NowozinMicrosoft Research (Cambridge, UK)Verified email at microsoft.com
Junichiro ShiomiThe University of TokyoVerified email at photon.t.u-tokyo.ac.jp
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
Jun SeseHumanome Lab Inc.Verified email at humanome.jp
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Atsuto SekoKyoto UniversityVerified email at cms.mtl.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	4313*	2001
Marginalized kernels between labeled graphs H Kashima, K Tsuda, A Inokuchi Proceedings of the 20th international conference on machine learning (ICML …, 2003	937	2003
Kernel methods in computational biology B Schölkopf, K Tsuda, JP Vert MIT press, 2004	819	2004
A primer on kernel methods JP Vert, K Tsuda, B Schölkopf Kernel methods in computational biology 47, 35-70, 2004	301	2004
Fast protein classification with multiple networks K Tsuda, H Shin, B Schölkopf Bioinformatics 21 (suppl_2), ii59-ii65, 2005	244	2005
Discriminative subsequence mining for action classification S Nowozin, G Bakir, K Tsuda 2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007	241	2007
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	239	2015
Marginalized kernels for biological sequences K Tsuda, T Kin, K Asai Bioinformatics 18 (suppl_1), S268-S275, 2002	239	2002
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	205	2005
A new discriminative kernel from probabilistic models K Tsuda, M Kawanabe, G Rätsch, S Sonnenburg, KR Müller Advances in Neural Information Processing Systems, 977-984, 2002	192	2002
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	163	2014
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	156	2009
Kernels for graphs H Kashima, K Tsuda, A Inokuchi Kernel methods in computational biology 39 (1), 101-113, 2004	154	2004
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	135	2017
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	134	2009
Learning kernels from biological networks by maximizing entropy K Tsuda, WS Noble Bioinformatics 20 (suppl_1), i326-i333, 2004	134	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	123	2007
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	116	2016
Support vector classifier with asymmetric kernel functions K Tsuda in European Symposium on Artificial Neural Networks (ESANN, 1999	112	1999
The em algorithm for kernel matrix completion with auxiliary data K Tsuda, S Akaho, K Asai Journal of machine learning research 4 (May), 67-81, 2003	109	2003

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