Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
This paper addresses the problem of recognizing shadows from monochromatic natural images. Without chromatic information, shadow classification is very challenging because the in...
Abstract. In this paper we present a novel approach to the graph isomorphism problem. We combine a direct approach, that tries to find a mapping between the two input graphs using...
Abstract— We present the Constrained Bi-directional RapidlyExploring Random Tree (CBiRRT) algorithm for planning paths in configuration spaces with multiple constraints. This al...
Dmitry Berenson, Siddhartha S. Srinivasa, Dave Fer...
—A novel formulation for optimal sensor selection and in-network fusion for distributed inference known as the prizecollecting data fusion (PCDF) is proposed in terms of optimal ...
Animashree Anandkumar, Meng Wang, Lang Tong, Anant...