Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
End-users increasingly find the need to perform light-weight, customized schema mapping. State-of-the-art tools provide powerful functions to generate schema mappings, but they u...
DTD and its instance have been considered the standard for data representation and information exchange format on the current web. However, when coming to the next generation of w...
Simulation studies are frequently used to evaluate new peer-to-peer searching techniques as well as existing techniques on new applications. Unless these studies are accurate in th...