There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a fixed order) with limited memory resources. In ...
Sumit Ganguly, Minos N. Garofalakis, Rajeev Rastog...
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...
— By combining a low-order model of forecast errors, the extended Kalman filter, and classical continuous optimization, we develop an integrated methodology for planning mobile ...
The purpose of this paper is to forecast the time evolution of a binary response variable from an associated continuous time series observed only at discrete time points that usual...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...