We propose new types of linguistic summaries of time-series data that extend those proposed in our previous papers. The proposed summaries of time series refer to the summaries of...
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
We have developed a computational framework to characterize social network dynamics in the blogosphere at individual, group and community levels. Such characterization could be us...
Munmun De Choudhury, Hari Sundaram, Ajita John, Do...
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
We tackle the problem of real-time statistical analysis of functional magnetic resonance imaging (fMRI) data. In a recent paper, we proposed an incremental algorithm based on the e...
Alexis Roche, Philippe Pinel, Stanislas Dehaene, J...