Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
We study the intrinsic difficulty of solving linear parabolic initial value problems numerically at a single point. We present a worst case analysis for deterministic as well as fo...
In this paper, we select the application domain of earthquake engineering for utility of sonification, where signals are of random frequency and amplitude content. In particular, ...
Lakshmy Ramaswamy, Tara C. Hutchinson, Falko Kuest...
We consider Bayesian detection/classification of discrete random parameters that are strongly dependent locally due to some deterministic local constraint. Based on the recently ...
Georg Kail, Jean-Yves Tourneret, Franz Hlawatsch, ...
We consider the following combinatorial auction: Given a range space (U, R), and m bidders interested in buying only ranges in R, each bidder j declares her bid bj : R R+. We give...
George Christodoulou, Khaled M. Elbassioni, Mahmou...