We present a branch-and-bound algorithm for minimizing a convex quadratic objective function over integer variables subject to convex constraints. In a given node of the enumerati...
Abstract-- The efficiency of distributed sensor networks depends on an optimal trade-off between the usage of resources and data quality. The work in this paper addresses the probl...
Amanda Prorok, Christopher M. Cianci, Alcherio Mar...
We consider the problem of distributed classification of multiple observations of the same object that are collected in an ad-hoc network of vision sensors. Assuming that each sen...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Proximal bundle methods have been shown to be highly successful optimization methods for unconstrained convex problems with discontinuous first derivatives. This naturally leads ...
Bioluminescence imaging (BLI) offers the possibility to study and image biology at molecular scale in small animals with applications in oncology or gene expression studies. Here ...
Mickael Savinaud, Martin de La Gorce, Serge Maitre...
In this paper, the global optimization problem with an objective function that is multiextremal that satisfies the Lipschitz condition over a hypercube is considered. An algorithm...
— The main aspect in multi-robot exploration is the efficient coordination of a group of robots. Inspired by previous results on the coverage problem, we propose a novel, fronti...
A. Dominik Haumann, Kim D. Listmann, Volker Willer...
Abstract. Modularity was introduced as a measure of goodness for the community structure induced by a partition of the set of vertices in a graph. Then, it also became an objective...
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...