We introduce a class of robust non-parametric estimation methods which are ideally suited for the reconstruction of signals and images from noise-corrupted or sparsely collected s...
Data-based control design methods most often consist of iterative adjustment of the controller's parameters towards the parameter values which minimize an H2 performance crit...
Alexandre S. Bazanella, Michel Gevers, Ljubisa Mis...
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...