The appropriate choice of a method for imputation of missing data becomes especially important when the fraction of missing values is large and the data are of mixed type. The prop...
Vadim V. Ayuyev, Joseph Jupin, Philip W. Harris, Z...
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...
In this paper, we study the problem of learning block classification models to estimate block functions. We distinguish general models, which are learned across multiple sites, an...
In Open Multi-Agent Systems (OMAS), deciding with whom to interact is a particularly difficult task for an agent, as repeated interactions with the same agents are scarce, and rep...
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...