Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
Push-based data delivery requires knowledge of user interests for making scheduling, bandwidthallocation, and routing decisions. Such information is maintained as user profiles. W...
: A series of genome-scale algorithms and high-performance implementations is described and shown to be useful in the genetic analysis of gene transcription. With them it is possib...