Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Relational database systems have been the dominating technology to manage and analyze large data warehouses. Moreover, the ER model, the standard in database design, has a close r...
Carlos Ordonez, Il-Yeol Song, Carlos Garcia-Alvara...
Thread-level speculation (TLS) has proven to be a promising method of extracting parallelism from both integer and scientific workloads, targeting speculative threads that range ...
Christopher B. Colohan, Anastassia Ailamaki, J. Gr...
Background: The availability of interaction databases provides an opportunity for researchers to utilize immense amounts of data exclusively in silico. Recently there has been an ...
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...