DDD: A NEW ENSEMBLE APPROACH FOR DEALING WITH CONCEPT DRIFT

DDD: A NEW ENSEMBLE APPROACH FOR DEALING WITH CONCEPT DRIFT Online learning algorithms often have to operate in the presence of concept drifts. A recent study revealed that different diversity levels in an ensemble of learning machines are required in order to maintain high generalization on both old and new concepts. Inspired by this study […]


ANO NIMOS: AN LP-BASED APPROACH FOR ANONYMIZING WEIGHTED SOCIAL NETWORK GRAPHS

ANO´NIMOS: AN LP-BASED APPROACH FOR ANONYMIZING WEIGHTED SOCIAL NETWORK GRAPHS The increasing popularity of social networks has initiated a fertile research area in information extraction and data mining. Anonymization of these social graphs is important to facilitate publishing these data sets for analysis by external entities. Prior work has concentrated mostly on node identity anonymization […]