This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
XCSF is a novel version of learning classifier systems (LCS) which extends the typical concept of LCS by introducing computable classifier prediction. In XCSF Classifier predictio...
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
NLP tasks are often domain specific, yet systems can learn behaviors across multiple domains. We develop a new multi-domain online learning framework based on parameter combinatio...