The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
We introduce the Multiplicative Update Selector and Estimator (MUSE) algorithm for sparse approximation in underdetermined linear regression problems. Given f = Φα∗ + µ, the ...
Abstract. We consider the problem of checking equivalence of conjunctive queries with inequalities under bag (multiset) semantics. The problem is known to be decidable in pspace an...
A classical learning problem in Inductive Inference consists of identifying each function of a given class of recursive functions from a finite number of its output values. Unifor...
The constraint paradigm provides powerful concepts to represent and solve different kinds of planning problems, e. g. factory scheduling. Factory scheduling is a demanding optimiz...