Previous studies have shown that array regrouping and structure splitting significantly improve data locality. The most effective technique relies on profiling every access to eve...
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
A lift curve, with the true positive rate on the y-axis and the customer pull (or contact) rate on the x-axis, is often used to depict the model performance in many data mining ap...
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...