We present a novel hybrid technique for improving the predictive performance of an online Machine Learning system: Combining advantages from both memory based and concept based pr...
Marcus-Christopher Ludl, Achim Lewandowski, Georg ...
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qi...
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...
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...