We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
For a wide variety of classification algorithms, scalability to large databases can be achieved by observing that most algorithms are driven by a set of sufficient statistics that...
"Oneperson's noise is another person's signal." For manyapplications, including the detection of credit card frauds and the monitoringof criminal activities in...
Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the fe...
The dimensionality reduction problem has been widely studied in the database literature because of its application for concise data representation in a variety of database applica...