In many classification tasks training data have missing feature values that can be acquired at a cost. For building accurate predictive models, acquiring all missing values is of...
Prem Melville, Foster J. Provost, Raymond J. Moone...
In supervised machine learning, the partitioning of the values (also called grouping) of a categorical attribute aims at constructing a new synthetic attribute which keeps the info...
Recently, the practice of speculation in resolving data dependences has been studied as a means of extracting more instruction level parallelism (ILP). An outcome of an instructio...
Multi-valued model-checking is an extension of classical model-checking to reasoning about systems with uncertain information, which are common during early design stages. The addi...
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...