We describe a physically-based Monte Carlo technique for approximating bidirectional reflectance distribution functions (BRDFs) for a large class of geometries by directly simulat...
Stephen H. Westin, James Arvo, Kenneth E. Torrance
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
: In this paper, we study the parameter estimation problem in a general heteroscedastic linear system, by putting the problem in the framework of the bilinear approach to low-rank ...
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
A central line of research in the area of PCPs is devoted to constructing short PCPs. In this paper, we show that if we allow an additional interactive verification phase, with v...