We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...
Predicting stock market movements is always difficult. Investors try to guess a stock's behavior, but it often backfires. Thumb rules and intuition seems to be the major indi...
This paper focuses on a technique to empower commercial-off-the-shelf (COTS) systems with an execution environment, and corresponding services, to support realtime and embedded ap...
Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targ...
Abdallah Sayyed-Ahmad, Kagan Tuncay, Peter J. Orto...
The aggregation and comparison of behavioral patterns on the WWW represent a tremendous opportunity for understanding past behaviors and predicting future behaviors. In this paper...
Eytan Adar, Daniel S. Weld, Brian N. Bershad, Stev...