27 search results - page 1 / 6 » Model Selection Under Covariate Shift |
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
A common assumption in supervised learning is that the training and test input points follow the same probability distribution. However, this assumption is not fulfilled, e.g., in...
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...
SIGPRO
2010
12 years 11 months ago
2010
In this paper, we propose a novel semi-supervised speaker identification method that can alleviate the influence of non-stationarity such as session dependent variation, the recor...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
UAI
2008
13 years 6 months ago
2008
Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of linearly ordered features, as one...