We present a geometric model and a computational method for segmentation of images with missing boundaries. In many situations, the human visual system fills in missing gaps in ed...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
Abstract--With the availability of powerful computational and communication systems, scientists now readily access large, complicated derived datasets and build on those results to...
Leon J. Osterweil, Lori A. Clarke, Aaron M. Elliso...
This paper shows how computational Riemannian manifold can be used to solve several problems in computer vision and graphics. Indeed, Voronoi segmentations and Delaunay graphs comp...