10 search results - page 1 / 2 » Direct Importance Estimation with Model Selection and Its Ap... |
NIPS
2007
13 years 6 months ago
2007
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...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
The importance estimation problem (estimating the ratio of two probability density functions) has recently gathered a great deal of attention for use in various applications, e.g....
SDM
2008
SIAM
13 years 6 months ago
2008
SIAM
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
ML
2012
ACM
12 years 14 days ago
2012
ACM
The ratio of two probability densities can be used for solving various machine learning tasks such as covariate shift adaptation (importance sampling), outlier detection (likeliho...
SDM
2009
SIAM
14 years 2 months ago
2009
SIAM
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...