Folgen
Masashi Sugiyama
Masashi Sugiyama
Sonstige Namen杉山 将
Director, RIKEN Center for Advanced Intelligence Project / Professor, The University of Tokyo
Bestätigte E-Mail-Adresse bei k.u-tokyo.ac.jp - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Dataset shift in machine learning
J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence
Mit Press, 2022
26182022
Co-teaching: Robust training of deep neural networks with extremely noisy labels
B Han, Q Yao, X Yu, G Niu, M Xu, W Hu, I Tsang, M Sugiyama
Advances in neural information processing systems 31, 2018
23472018
Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis.
M Sugiyama
Journal of machine learning research 8 (5), 2007
13502007
Covariate shift adaptation by importance weighted cross validation.
M Sugiyama, M Krauledat, KR Müller
Journal of Machine Learning Research 8 (5), 2007
11572007
Direct importance estimation with model selection and its application to covariate shift adaptation
M Sugiyama, S Nakajima, H Kashima, P Buenau, M Kawanabe
Advances in neural information processing systems 20, 2007
10912007
How does disagreement help generalization against label corruption?
X Yu, B Han, J Yao, G Niu, I Tsang, M Sugiyama
International conference on machine learning, 7164-7173, 2019
8582019
Density ratio estimation in machine learning
M Sugiyama, T Suzuki, T Kanamori
Cambridge University Press, 2012
7212012
Change-point detection in time-series data by relative density-ratio estimation
S Liu, M Yamada, N Collier, M Sugiyama
Neural Networks 43, 72-83, 2013
6272013
A least-squares approach to direct importance estimation
T Kanamori, S Hido, M Sugiyama
The Journal of Machine Learning Research 10, 1391-1445, 2009
6242009
Machine learning in non-stationary environments: Introduction to covariate shift adaptation
M Sugiyama, M Kawanabe
MIT press, 2012
5722012
Learning discrete representations via information maximizing self-augmented training
W Hu, T Miyato, S Tokui, E Matsumoto, M Sugiyama
International conference on machine learning, 1558-1567, 2017
5642017
Positive-unlabeled learning with non-negative risk estimator
R Kiryo, G Niu, MC Du Plessis, M Sugiyama
Advances in neural information processing systems 30, 2017
5592017
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, 699-746, 2008
5222008
Change-point detection in time-series data by direct density-ratio estimation
Y Kawahara, M Sugiyama
Proceedings of the 2009 SIAM international conference on data mining, 389-400, 2009
5212009
Local fisher discriminant analysis for supervised dimensionality reduction
M Sugiyama
Proceedings of the 23rd international conference on Machine learning, 905-912, 2006
4792006
Attacks which do not kill training make adversarial learning stronger
J Zhang, X Xu, B Han, G Niu, L Cui, M Sugiyama, M Kankanhalli
International conference on machine learning, 11278-11287, 2020
4702020
Analysis of learning from positive and unlabeled data
MC Du Plessis, G Niu, M Sugiyama
Advances in neural information processing systems 27, 2014
4552014
Active learning in recommender systems
N Rubens, M Elahi, M Sugiyama, D Kaplan
Recommender systems handbook, 809-846, 2015
4182015
Are anchor points really indispensable in label-noise learning?
X Xia, T Liu, N Wang, B Han, C Gong, G Niu, M Sugiyama
Advances in neural information processing systems 32, 2019
4042019
Convex formulation for learning from positive and unlabeled data
M Du Plessis, G Niu, M Sugiyama
International conference on machine learning, 1386-1394, 2015
3862015
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20