We have developed a new statistical timing analysis approach that does not impose any assumptions on the nature of manufacturing variability and takes into account an arbitrary mo...
Jennifer L. Wong, Azadeh Davoodi, Vishal Khandelwa...
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
In this paper, we present a probabilistic formulation of kernel-based tracking methods based upon maximum likelihood estimation. To this end, we view the coordinates for the pixel...
Quang Anh Nguyen, Antonio Robles-Kelly, Chunhua Sh...
A statistical framework for modeling and prediction of binary matrices is presented. The method is applied to social network analysis, specifically the database of US Supreme Cou...
Eric Wang, Jorge Silva, Rebecca Willett, Lawrence ...