Abstract. Existing algorithms for regular inference (aka automata learning) allows to infer a finite state machine by observing the output that the machine produces in response to ...
An important extension of satisfiability testing is model-counting, a task that corresponds to problems such as probabilistic reasoning and computing the permanent of a Boolean ma...
In this paper, we investigate how to modify the Naive Bayes classifier in order to perform classification that is restricted to be independent with respect to a given sensitive att...
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
Background: New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time,...