Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
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 ...
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Look-up table based FPGAs have migrated from a niche technology for design prototyping to a valuable end-product component and, in some cases, a replacement for general purpose pr...
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...