206,915 research outputs found
A Novel Convex Relaxation for Non-Binary Discrete Tomography
We present a novel convex relaxation and a corresponding inference algorithm
for the non-binary discrete tomography problem, that is, reconstructing
discrete-valued images from few linear measurements. In contrast to state of
the art approaches that split the problem into a continuous reconstruction
problem for the linear measurement constraints and a discrete labeling problem
to enforce discrete-valued reconstructions, we propose a joint formulation that
addresses both problems simultaneously, resulting in a tighter convex
relaxation. For this purpose a constrained graphical model is set up and
evaluated using a novel relaxation optimized by dual decomposition. We evaluate
our approach experimentally and show superior solutions both mathematically
(tighter relaxation) and experimentally in comparison to previously proposed
relaxations
Structural matching by discrete relaxation
This paper describes a Bayesian framework for performing relational graph matching by discrete relaxation. Our basic aim is to draw on this framework to provide a comparative evaluation of a number of contrasting approaches to relational matching. Broadly speaking there are two main aspects to this study. Firstly we locus on the issue of how relational inexactness may be quantified. We illustrate that several popular relational distance measures can be recovered as specific limiting cases of the Bayesian consistency measure. The second aspect of our comparison concerns the way in which structural inexactness is controlled. We investigate three different realizations ai the matching process which draw on contrasting control models. The main conclusion of our study is that the active process of graph-editing outperforms the alternatives in terms of its ability to effectively control a large population of contaminating clutter
A nonlinear discrete-velocity relaxation model for traffic flow
We derive a nonlinear 2-equation discrete-velocity model for traffic flow
from a continuous kinetic model. The model converges to scalar
Lighthill-Whitham type equations in the relaxation limit for all ranges of
traffic data. Moreover, the model has an invariant domain appropriate for
traffic flow modeling. It shows some similarities with the Aw-Rascle traffic
model. However, the new model is simpler and yields, in case of a concave
fundamental diagram, an example for a totally linear degenerate hyperbolic
relaxation model. We discuss the details of the hyperbolic main part and
consider boundary conditions for the limit equations derived from the
relaxation model. Moreover, we investigate the cluster dynamics of the model
for vanishing braking distance and consider a relaxation scheme build on the
kinetic discrete velocity model. Finally, numerical results for various
situations are presented, illustrating the analytical results
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