In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
The increasing complexity of configurable software systems creates a need for more intelligent sampling mechanisms to detect and locate failure-inducing dependencies between confi...
Adam A. Porter, Myra B. Cohen, Sandro Fouché...
Classification of time series has been attracting great interest over the past decade. Recent empirical evidence has strongly suggested that the simple nearest neighbor algorithm ...
Social network-based systems usually suffer from two major limitations: they tend to rely on a single data source (e.g. email traffic), and the form of network patterns is often p...
Yevgeniy Eugene Medynskiy, Nicolas Ducheneaut, Aym...
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...