Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
Jennifer Listgarten, Radford M. Neal, Sam T. Rowei...
We propose a method that detects the true direction of time series, by fitting an autoregressive moving average model to the data. Whenever the noise is independent of the previou...
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
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...
The Internet is witnessing explosive growth in traffic due to bulk content transfers, such as multimedia and software downloads, and online sharing of personal, commercial, and sc...
Massimiliano Marcon, Nuno Santos, P. Krishna Gumma...