Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
: We propose a domain-based classification method to predict protein-protein interactions using probabilities of putative interacting domain pairs derived from both experimentally-...
In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...
Experience sampling has been employed for decades to collect assessments of subjects' intentions, needs, and affective states. In recent years, investigators have employed au...
For highest performance, a modern microprocessor must be able to determine if an instruction is ready in the same cycle in which it is to be selected for execution. This creates a...