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SDM
2010
SIAM
165views Data Mining» more  SDM 2010»
14 years 15 days ago
Direct Density Ratio Estimation with Dimensionality Reduction
Methods for directly estimating the ratio of two probability density functions without going through density estimation have been actively explored recently since they can be used...
Masashi Sugiyama, Satoshi Hara, Paul von Büna...
NN
2010
Springer
183views Neural Networks» more  NN 2010»
13 years 9 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui
NIPS
2007
14 years 14 days ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
JMLR
2010
173views more  JMLR 2010»
13 years 5 months ago
Conditional Density Estimation via Least-Squares Density Ratio Estimation
Estimating the conditional mean of an inputoutput relation is the goal of regression. However, regression analysis is not sufficiently informative if the conditional distribution ...
Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki, T...
CVPR
2007
IEEE
15 years 1 months ago
Trace Ratio vs. Ratio Trace for Dimensionality Reduction
A large family of algorithms for dimensionality reduction end with solving a Trace Ratio problem in the form of arg maxW Tr(WT SpW)/Tr(WT SlW)1 , which is generally transformed in...
Huan Wang, Shuicheng Yan, Dong Xu, Xiaoou Tang, Th...