Digital tomosynthesis imaging is becoming increasingly significant in a variety of medical imaging applications. Tomosynthesis imaging involves the acquisition of a series of proj...
Julianne Chung, James G. Nagy, Ioannis Sechopoulos
In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of ins...
A fundamental building block of many data mining and analysis approaches is density estimation as it provides a comprehensive statistical model of a data distribution. For that re...
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...