We propose a general class of label configuration priors for continuous multi-label optimization problems. In contrast to MRF-based approaches, the proposed framework unifies label configuration energies such as minimum description length priors, co-occurrence priors and hierarchical label cost priors. Moreover, it does not require any preprocessing in terms of super-pixel estimation. All probl...

This paper investigates the general problem of resource allocation for mitigating channel fading effects in Free Space Optical (FSO) communications. The is modeled as constrained stochastic optimization framework, which covers a variety FSO scenarios involving power adaptation, relay selection and their joint allocation. Under this we propose two algorithms that solve problems. We first present...

We view the optimal single commodity network flow problem with linear arc costs and its dual as a pair of monotropic programming problems, i.e. problems of minimizing the separable sum of scalar extended real-valued convex functions over a subspace. For such problems directions of cost improvement can be selected from among a finite set of directions--the elementary vectors of the constraint su...

An algorithm for minimizing a nonlinear function subject to nonlinear inequality constraints is described It applies sequential quadratic programming techniques to a sequence of barrier problems and uses trust regions to ensure the robustness of the iteration and to allow the direct use of second order derivatives This framework permits primal and primal dual steps but the paper focuses on the ...