2363 search results - page 2 / 473 » Learning Algorithms for Domain Adaptation |
CIKM
2009
Springer
13 years 12 months ago
2009
Springer
Adapting to rank address the the problem of insufficient domainspecific labeled training data in learning to rank. However, the initial study shows that adaptation is not always...
ICASSP
2007
IEEE
13 years 11 months ago
2007
IEEE
One of the main dif culties in echo cancellation is the fact that the learning rate needs to vary according to conditions such as double-talk and echo path change. Several methods...
NIPS
2007
13 years 6 months ago
2007
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
IJAR
2008
13 years 5 months ago
2008
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
JMLR
2012
11 years 7 months ago
2012
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...