Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
In this paper, we design and implement an efficient technique for parallel evidence propagation on state-of-the-art multicore processor systems. Evidence propagation is a major ste...
Abstract. Gradient-domain compositing is an essential tool in computer vision and its applications, e.g., seamless cloning, panorama stitching, shadow removal, scene completion and...
The demand for an efficient fault tolerance system has led to the development of complex monitoring infrastructure, which in turn has created an overwhelming task of data and even...
In this paper we investigate some properties and algorithms related to a text sparsification technique based on the identification of local maxima in the given string. As the numb...
Pierluigi Crescenzi, Alberto Del Lungo, Roberto Gr...