3 search results - page 1 / 1 » Learning Inter-Task Transferability in the Absence of Target... |
NIPS
2008
13 years 6 months ago
2008
We address the problem of learning classifiers for several related tasks that may differ in their joint distribution of input and output variables. For each task, small
ACCV
2010
Springer
12 years 11 months ago
2010
Springer
Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...
DAGM
2011
Springer
12 years 4 months ago
2011
Springer
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...