Shinichi Nakajima

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Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoAdresse e-mail validée de k.u-tokyo.ac.jp
Klaus-Robert MüllerTU Berlin & Korea University & MPII & Google BrainAdresse e-mail validée de tu-berlin.de
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalAdresse e-mail validée de atr.jp
S. Derin BabacanAmazonAdresse e-mail validée de amazon.com
Wojciech SamekHead of AI Department and Explainable AI Group, Fraunhofer HHI, GermanyAdresse e-mail validée de hhi.fraunhofer.de
Hisashi KashimaProfessor, Kyoto UniversityAdresse e-mail validée de i.kyoto-u.ac.jp
Marius KloftTU KaiserslauternAdresse e-mail validée de cs.uni-kl.de
Paul von Bünauidalab GmbHAdresse e-mail validée de idalab.de
Ryota TomiokaMicrosoft Research CambridgeAdresse e-mail validée de microsoft.com
Tsuyoshi IdeIBM T. J. Watson Research CenterAdresse e-mail validée de us.ibm.com
Alexander BinderAssociate Professor, University of Oslo (UiO)Adresse e-mail validée de ifi.uio.no
Jun SeseHumanome Lab Inc.Adresse e-mail validée de humanome.jp
Ulf BrefeldLeuphana Universität LüneburgAdresse e-mail validée de leuphana.de
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyAdresse e-mail validée de tu-berlin.de
Christoph LippertProfessor, Hasso Plattner Institute, Universität PotsdamAdresse e-mail validée de hpi.de
Stephan MandtAssistant Professor, University of California, IrvineAdresse e-mail validée de uci.edu
John CunninghamAssociate Professor, Columbia UniversityAdresse e-mail validée de columbia.edu
Takeuchi IchiroProfessor of Computer Science, Nagoya Institute of TechnologyAdresse e-mail validée de nitech.ac.jp
Kazuho WatanabeToyohashi University of TechnologyAdresse e-mail validée de cs.tut.ac.jp

Shinichi Nakajima

Machine Learning Group, Technische Universität Berlin

Adresse e-mail validée de tu-berlin.de - Page d'accueil

Machine Learning Computer Vision


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation. M Sugiyama, S Nakajima, H Kashima, P Von Buenau, M Kawanabe NIPS 7, 1433-1440, 2007	732	2007
Semi-supervised local Fisher discriminant analysis for dimensionality reduction M Sugiyama, T Idé, S Nakajima, J Sese Machine learning 78 (1), 35-61, 2010	321	2010
Direct importance estimation for covariate shift adaptation M Sugiyama, T Suzuki, S Nakajima, H Kashima, P von Bünau, ... Annals of the Institute of Statistical Mathematics 60 (4), 699-746, 2008	291	2008
Multi-class image segmentation using conditional random fields and global classification N Plath, M Toussaint, S Nakajima Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	120	2009
Bayesian group-sparse modeling and variational inference SD Babacan, S Nakajima, MN Do IEEE transactions on signal processing 62 (11), 2906-2921, 2014	104	2014
Pool-based active learning in approximate linear regression M Sugiyama, S Nakajima Machine Learning 75 (3), 249-274, 2009	75	2009
Global analytic solution of fully-observed variational Bayesian matrix factorization S Nakajima, M Sugiyama, SD Babacan, R Tomioka Journal of Machine Learning Research 14 (Jan), 1-37, 2013	73	2013
Theoretical analysis of Bayesian matrix factorization S Nakajima, M Sugiyama The Journal of Machine Learning Research 12, 2583-2648, 2011	51	2011
Nikon Multimedia Event Detection System. T Matsuo, S Nakajima TRECVID, 2010	40	2010
Perfect Dimensionality Recovery by Variational Bayesian PCA. S Nakajima, R Tomioka, M Sugiyama, SD Babacan NIPS, 980-988, 2012	31	2012
Variational Bayes solution of linear neural networks and its generalization performance S Nakajima, S Watanabe Neural Computation 19 (4), 1112-1153, 2007	31	2007
On Bayesian PCA: Automatic dimensionality selection and analytic solution S Nakajima, M Sugiyama, SD Babacan ICML, 2011	28	2011
Implicit Regularization in Variational Bayesian Matrix Factorization. S Nakajima, M Sugiyama ICML, 2010	26	2010
Towards best practice in explaining neural network decisions with LRP M Kohlbrenner, A Bauer, S Nakajima, A Binder, W Samek, S Lapuschkin 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020	25	2020
Multiple kernel learning for object classification S Nakajima, A Binder, C Müller, W Wojcikiewicz, M Kloft, U Brefeld, ... Proceedings of the 12th Workshop on Information-based Induction Sciences 24, 2009	24	2009
An exhaustive search and stability of sparse estimation for feature selection problem K Nagata, J Kitazono, S Nakajima, S Eifuku, R Tamura, M Okada IPSJ Online Transactions 8, 25-32, 2015	22	2015
Support Vector Data Descriptions and-Means Clustering: One Class? N Görnitz, LA Lima, KR Müller, M Kloft, S Nakajima IEEE transactions on neural networks and learning systems 29 (9), 3994-4006, 2017	20	2017
Variational Bayesian sparse additive matrix factorization S Nakajima, M Sugiyama, SD Babacan Machine learning 92 (2-3), 319-347, 2013	19	2013
Probabilistic Low-Rank Subspace Clustering. SD Babacan, S Nakajima, MN Do NIPS, 2753-2761, 2012	19	2012
Global analytic solution for variational Bayesian matrix factorization S Nakajima, M Sugiyama, R Tomioka Advances in Neural Information Processing Systems 23, 1768-1776, 2010	19	2010

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