Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast mo...
One approach to modeling structured discrete data is to describe the probability of states via an energy function and Gibbs distribution. A recurring difficulty in these models is...
Daniel Tarlow, Ryan Prescott Adams, Richard S. Zem...
We consider the problem of estimating a deterministic sparse vector x0 from underdetermined measurements Ax0 +w, where w represents white Gaussian noise and A is a given determinis...
We consider the performance of a simple greedy matching algorithm MINGREEDY when applied to random cubic graphs. We show that if λn is the expected number of vertices not matched...
In this paper we will consider tight upper- and lower-bounds on the weight of the optimal matching for random point sets distributed among the leaves of a tree, as a function of it...