Koji Tsuda

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Citations	17033	6875
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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH ZürichVerified email at tuebingen.mpg.de
Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
Kiyoshi AsaiProfessor of Computational Biology, University of TokyoVerified email at k.u-tokyo.ac.jp
Hisashi KashimaProfessor, Kyoto UniversityVerified email at i.kyoto-u.ac.jp
Sebastian MikaVerified email at sebastianmika.info
Jean-Philippe VertOwkin / PSL UniversityVerified email at mines-paristech.fr
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Junichiro ShiomiThe University of TokyoVerified email at photon.t.u-tokyo.ac.jp
Ichigaku TakigawaKyoto University / Hokkaido UniversityVerified email at kyoto-u.ac.jp
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Yasuo TabeiUnit leader at RIKEN-AIPVerified email at riken.go.jp
Takeaki UnoNational Institute of Informatics, JapanVerified email at nii.jp
Akihiro InokuchiProfessor, Kwansei Gakuin UniversityVerified email at kwansei.ac.jp
Sebastian NowozinDeepMindVerified email at deepmind.com
Takeuchi IchiroProfessor, Nagoya UniversityVerified email at mae.nagoya-u.ac.jp
Tsuyoshi Kato群馬大学Verified email at cs.gunma-u.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
Teruyasu MizoguchiInstitute of Industrial Science, The University of TokyoVerified email at iis.u-tokyo.ac.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	4815*	2001
Marginalized kernels between labeled graphs H Kashima, K Tsuda, A Inokuchi Proceedings of the 20th international conference on machine learning (ICML …, 2003	1105	2003
Kernel methods in computational biology B Schölkopf, K Tsuda, JP Vert MIT press, 2004	985	2004
A primer on kernel methods JP Vert, K Tsuda, B Schölkopf Kernel methods in computational biology 47, 35-70, 2004	524	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	411	2015
Bayesian inference and optimal design in the sparse linear model M Seeger, F Steinke, K Tsuda Artificial Intelligence and Statistics, 444-451, 2007	370	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	290	2017
Fast protein classification with multiple networks K Tsuda, H Shin, B Schölkopf Bioinformatics 21 (suppl_2), ii59-ii65, 2005	280	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	278	2016
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	267	2014
Marginalized kernels for biological sequences K Tsuda, T Kin, K Asai Bioinformatics 18 (suppl_1), S268-S275, 2002	264	2002
Discriminative subsequence mining for action classification S Nowozin, G Bakir, K Tsuda 2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007	259	2007
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	243	2005
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	210	2017
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	208	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	183	2009
Kernels for graphs H Kashima, K Tsuda, A Inokuchi Kernel methods in computational biology, 155-170, 2004	175	2004
gBoost: a mathematical programming approach to graph classification and regression H Saigo, S Nowozin, T Kadowaki, T Kudo, K Tsuda Machine Learning 75, 69-89, 2009	150	2009
Learning kernels from biological networks by maximizing entropy K Tsuda, WS Noble Bioinformatics 20 (suppl_1), i326-i333, 2004	146	2004
Ultranarrow-band wavelength-selective thermal emission with aperiodic multilayered metamaterials designed by Bayesian optimization A Sakurai, K Yada, T Simomura, S Ju, M Kashiwagi, H Okada, T Nagao, ... ACS central science 5 (2), 319-326, 2019	137	2019

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