Abstract. A number of techniques are described for solving sparse linear systems on parallel platforms. The general approach used is a domaindecomposition type method in which a pr...
An open problem in Simultaneous Localization and Mapping (SLAM) is the development of algorithms which scale with the size of the environment. A few promising methods exploit the ...
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
We propose a new method for matching two 3D point sets of identical cardinality with global similarity but local non-rigid deformations and distribution errors. This problem arises...
Sparse matrix operations achieve only small fractions of peak CPU speeds because of the use of specialized, indexbased matrix representations, which degrade cache utilization by i...