The problem of designing input signals for optimal generalization in supervised learning is called active learning. In many active learning methods devised so far, the bias of the...
The data structures suitable for indexing of large spatial objects in databases are considered. Some generalizations of existing tree methods concerned approximation of spatial ob...
In this paper, we investigate the problem of deriving precision estimates for bootstrap quantities within parametric families. Efron's [1992] jackknife-after-bootstrap is a s...
We propose a new semi-supervised model selection method that is derived by applying the structural risk minimization principle to a recent semi-supervised generalization error bou...
Abstract—We investigate the scalability of the hypergraphbased sparse matrix partitioning methods with respect to the increasing sizes of matrices and number of nonzeros. We prop...