We present a novel approach for analyzing two-dimensional (2D) flow field data based on the idea of invariant moments. Moment invariants have traditionally been used in computer vi...
Michael Schlemmer, Manuel Heringer, Florian Morr...
Abstract--Recent advances in network coding research dramatically changed the underlying structure of optimal multicast routing algorithms and made them efficiently computable. Whi...
We describe computationally efficient methods for learning mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs). We argue that simple...
Bo Thiesson, Christopher Meek, David Maxwell Chick...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Lubrication equations describe many structuring processes of thin liquid films. We develop and apply a numerical framework suitable for their analysis employing a dynamical systems...