We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
In the previous papers (Pupeikis, 2000; Genov et al., 2006; Atanasov and Pupeikis, 2009), a direct approach for estimating the parameters of a discrete-time linear time-invariant (...
Recently a class of multiscale stochastic models has been introducedin which Gaussian random processes are described by scale-recursive dynamics that are indexed by the nodes of a...
Paul W. Fieguth, William W. Irving, Alan S. Willsk...
The problem of finding the most appropriate subset of features or regressors is the generic challenge of Machine Learning problems like regression estimation or pattern recognitio...
This paper addresses two aspects of low-power design for FPGA circuits. First, we present an RT-level power estimator for FPGAs with consideration of wire length. The power estima...