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Here, I review facts that are most probably known, namely that the information gain criterion used to drive experimental design in a linear-Gaussian model is submodular, so that a well-known approximation guarantee holds for the sequential greedy algorithm ...
Dense three-dimensional reconstruction of a scene from images is a challenging task. Usually, it is achieved by finding correspondences in successive images and computing the distance by means of epipolar geometry. In this paper, we propose a variational f ...
In this paper, we present a decentralized algorithm to find minimum cost quality of service (QoS) flow subgraphs in network coded multicast schemes. The main objective is to find minimum cost subgraphs that also satisfy user-specified QoS constraints, spec ...
In this work we present a new greedy algorithm for sparse approximation called LocOMP. LocOMP is meant to be run on local dictionaries made of atoms with much shorter supports than the signal length. This notably encompasses shift-invariant dictionaries an ...
In the distributed linear source coding problem, a set of distributed sensors observe subsets of a data vector with noise, and provide the fusion center linearly encoded data. The goal is to determine the encoding matrix of each sensor such that the fusion ...
Given a geometric hypergraph (or a range-space) H=(V,E), a coloring of its vertices is said to be conflict-free if for every hyperedge S∈E there is at least one vertex in S whose color is distinct from the colors of all other vertices i ...
Navigability of networks, that is, the ability to find any given destination vertex starting from any other vertex, is crucial to their usefulness. In 2000 Kleinberg showed that optimal navigability could be achieved in small world networks provided that a ...
The last decade has witnessed a fundamental change in the role of network theory. Side by side with the increasing relevance of interdisciplinarity, this ensemble of mathematical tools and methods has known such a success and such a wide range of different ...
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals; instead of taking periodic samples, we measure inner products with All < N random vectors and then recover the signal via a sparsity-s ...
This paper presents a receiver-driven video delivery algorithm that exploits a novel Randomized Network Coding (RNC) scheme for unequal error protection (UEP). The main idea of our approach is to account for the unequal importance of media packets in the n ...
