Let {Sm} be an infinite sequence whose limit or antilimit S can be approximated very efficiently by applying a suitable extrapolation method E0 to {Sm}. Assume that the Sm and henc...
In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...
To approximate convolutions which occur in evolution equations with memory terms, a variable-stepsize algorithm is presented for which advancing N steps requires only O(N log N) op...
We consider the following network design problem. We are given an undirected network with costs on the edges, a set of terminals, and an upper bound for each terminal limiting the ...
Samuel Fiorini, Gianpaolo Oriolo, Laura Sanit&agra...
We introduce a new algorithm based on linear programming that approximates the differential value function of an average-cost Markov decision process via a linear combination of p...