Variational models for image segmentation have many applications, but can be slow to compute. Recently, globally convex segmentation models have been introduced which are very rel...
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...
Many practical data streams are typically composed of several states known as regimes. In this paper, we invoke phase space reconstruction methods from non-linear time series and ...
We propose a novel Riemannian framework for comparing signals and images in a manner that is invariant to their levels of blur. This framework uses a log-Fourier representation of...
Zhengwu Zhang, Eric Klassen, Anuj Srivastava, Pava...
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...