Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
In this paper we consider the p-ary transitive reduction (TRp) problem where p > 0 is an integer; for p = 2 this problem arises in inferring a sparsest possible (biological) sig...
Graph based semi-supervised learning (SSL) methods play an increasingly important role in practical machine learning systems. A crucial step in graph based SSL methods is the conv...
Abstract—The purpose of this study is to investigate multiregion graph cut image partitioning via kernel mapping of the image data. The image data is transformed implicitly by a ...
Although steady progress has been made in recent stereo algorithms, producing accurate results in the neighborhood of depth discontinuities remains a challenge. Moreover, among th...