In this paper we propose a novel algorithm that provides bounded approximate solutions for decentralised coordination problems. Our approach removes cycles in any general constraint network by eliminating dependencies between functions and variables which have the least impact on the solution quality. It uses the max-sum algorithm to optimally solve the resulting tree structured constraint netw...

An adaptive servomechanism is developed in the context of the problem of approximate or practical tracking (with prescribed asymptotic accuracy), by the system output, of any admissible reference signal (absolutely continuous and bounded with essentially bounded derivative) for every member of a class of controlled dynamical systems modelled by functional differential equations.

We study the problem of reconstructing a hidden graph given access to a distance oracle. We design randomized algorithms for the following problems: reconstruction of a degree bounded graph with query complexity Õ(n); reconstruction of a degree bounded outerplanar graph with query complexity Õ(n); and near-optimal approximate reconstruction of a general graph.

In this paper, we study the problem of learning the structure of Markov Networks that permit efficient inference. We formulate structure learning as an optimization problem that maximizes the likelihood of the model such that the inference complexity on the resulting structure is bounded. The inference complexity is measured with respect to any chosen algorithm (either exact or approximate), or...

In this paper, the artificial boundary method for Poisson problem in an infinite domain with a concave angle is investigated. The exact and approximate elliptical arc artificial boundary conditions are given. The finite element approximation is formulated in a bounded domain using the approximate artificial boundary condition and error estimates are obtained. Finally, some numerical examples sh...