Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...
High performance computers currently under construction, such as IBM’s Blue Gene/L, consisting of large numbers (64K) of low cost processing elements with relatively small local...
Ed Upchurch, Paul L. Springer, Maciej Brodowicz, S...
Matching and searching computations play an important role in the indexing of data. These computations are typically encoded in very tight loops with a single index variable and a...
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...