Median averaging is a powerful averaging concept on sets of vector data in finite dimensions. A generalization of the median for shapes in the plane is introduced. The underlying ...
Abstract. We propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time...
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
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...
In recent years, compositional modeling and selfexplanatory simulation techniques have simplified the process of building dynamic simulators of physical systems. Building steady-s...