Traditional binary hypothesis testing relies on the precise knowledge of the probability density of an observed random vector conditioned on each hypothesis. However, for many app...
Abstract. In this paper we study the problem of determining threedimensional orientations for noisy projections of randomly oriented identical particles. The problem is of central ...
Consider a scenario where one desires to simulate the execution of some graph algorithm on random input graphs of huge, perhaps even exponential size. Sampling and storing these h...
In this paper, we present a new Adaptive Scale Kernel Consensus (ASKC) robust estimator as a generalization of the popular and state-of-the-art robust estimators such as RANSAC (R...