In this paper we apply the well known sample average approximation (SAA) method to solve a class of stochastic variational inequality problems (SVIPs). We investigate the existenc...
Transform approximations are explored for speeding up the software compression of images and video. Approximations are used to replace the regular discrete cosine transform (DCT) w...
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
The representation of moving geometry entities is an important issue in the fields of CAD/CAM and robotics motion design. We present a method to interpolate the moving frame homog...
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...