Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
Standard detection algorithms for nonlinearity linkage fail when applied to typical problems in the analysis of financial time-series data. We explain how this failure arises whe...
We describe our investigations in generating textual summaries of physiological time series data to aid medical personnel in monitoring babies in neonatal intensive care units. Ou...
Somayajulu Sripada, Ehud Reiter, Jim Hunter, Jin Y...
We are developing technology for generating English textual summaries of time-series data, in three domains: weather forecasts, gas-turbine sensor readings, and hospital intensive...
Somayajulu Sripada, Ehud Reiter, Jim Hunter, Jin Y...
Prediction of financial time series using artificial neural networks has been the subject of many publications, even if the predictability of financial series remains a subject of ...
Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vinc...