Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
This research reports on exploring analytical methodologies for spatio-temporal data of pedestrian egress dynamics in a crowded environment. The research objective is to spatially...
Prior work has shown that reduced, ordered, binary decision diagrams (BDDs) can be a powerful tool for program trace analysis and visualization. Unfortunately, it can take hours o...
In software evolution analysis, many approaches analyze release history data available through versioning systems. The recent investigations of CVS data have shown that commonly c...