Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Space-varying convolution often arises in the modeling or restoration of images captured by optical imaging systems. For example, in applications such as microscopy or photography...
Jianing Wei, Guangzhi Cao, Charles A. Bouman, Jan ...
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
We are presenting a text analysis tool set that allows analysts in various fields to sieve through large collections of multilingual news items quickly and to find information that...
Abstract This paper is about tool support for knowledgeintensive engineering tasks. In particular, it introduces software technology to assist the design of complex technical syste...