In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
In recent literature it is commonly agreed that the first phase of the software development process is still an area of concern. Furthermore, while software technology has been ch...
Abstract: We propose a framework for the specification of extensible database systems. A particular goal is to implement a software component for parsing and rule-based optimizatio...
Nowadays, organizations face with a very high competitiveness and for this reason they have to continuously improve their processes. Two key aspects to be considered in the softwa...
This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
Shrihari Vasudevan, Fabio T. Ramos, Eric Nettleton...