Research Project
Grant-in-Aid for Young Scientists (Start-up)
We developed an approximate inference method for the constrained exponential-family mixture models that are used for the simultaneous dimensionality reduction and clustering of high-dimensional data. It was applied to the hand-written digit recognition task and its effectiveness was demonstrated. We also derived an approximate inference method for the varying binomial process that efficiently estimates the varying probabilities of some event. Furthermore, we demonstrated the general framework and the information-theoretic view of the local variational approximation.
All 2010 2009 2008 Other
All Journal Article (9 results) (of which Peer Reviewed: 9 results) Presentation (14 results) Remarks (3 results)
電子情報通信学会論文誌a J93-A
Pages: 326-330
110007610187
電子情報通信学会論文誌A J93-A
Studies in Classification, Data Analysis, and Knowledge Organization (Proceedings of the 11th IFCS Biennial Conference) (印刷中)
IEEE Transactions on Neural Networks vol.20
Pages: 1783-1796
IEICE Transactions on Information and Systems vol.E92-D
Pages: 1362-1368
10026810113
IEICE Transactions on Information and Systems E92-D
IEEE Transactions on Neural Networks 20
Proc.of ICONIP 2008, Part I, Lecture Notes in Computer Science 5506
Pages: 655-662
統計数理 (掲載確定)
120006019313
http://hawaii.naist.jp/~wkazuho/
http://mns.k.u-tokyo.ac.Jp/~kazuho/list-e.html