Temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. Several methods have been developed to explicitly construct te...
— As the technology scales into 90nm and below, process-induced variations become more pronounced. In this paper, we propose an efficient stochastic method for analyzing the vol...
Models of real world systems are being increasingly generated from data that describes the behaviour of systems. Data mining techniques, such as Artificial Neural Networks (ANN),...
Empirical studies of the variation in debt ratios across firms have used statistical models singularly to analyze the important determinants of capital structure. Researchers, how...
Permutation ambiguity is an inherent limitation in independent component analysis, which is a bottleneck in frequency-domain methods of convolutive source separation. In this pape...