Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
We present a reduction method that reduces a graph to a smaller core graph which behaves invariant with respect to planarity measures like crossing number, skewness, and thickness....
We present an approach for large-scale modeling of parametric surfaces using spherical harmonics (SHs). A standard least square fitting (LSF) method for SH expansion is not scala...
Abstract. We propose two differential geometric representations of planar shapes using: (i) direction functions and (ii) curvature functions, of their boundaries. Under either rep...
Anuj Srivastava, Washington Mio, Eric Klassen, Sha...
We propose a novel model of visual contrast measurement based on segregated ON and OFF pathways. Two driving forces have shaped our investigation: (1) establishing a mechanism sele...