Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
Trusted Computing gives rise to a new supply of trusted third parties on which distributed systems can potentially rely. They are the secure system components (hardware and softwa...
Spiral Architecture is a relatively new and powerful approach to general purpose machine vision system. It contains very useful geometric and algebraic properties. Two algebraic o...
In this paper, we present an efficient way to denoise bivariate data like height fields, color pictures or vector fields, while preserving edges and other features. Mixing surface...