Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
Current approaches for answering queries with imprecise constraints require users to provide distance metrics and importance measures for attributes of interest. In this paper we ...
In this paper, we propose novel algorithms for total variation (TV) based image restoration and parameter estimation utilizing variational distribution approximations. Within the h...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
Wavelet neural networks (WNN) have recently attracted great interest, because of their advantages over radial basis function networks (RBFN) as they are universal approximators bu...
In [1] Optimal Control methods over re-parametrization for curve and surface design were introduced. The advantage of Optimal Control over Global Minimization such as in [17] is t...