This article reviews recent advances in convex optimization algorithms for Big Data, which aim to reduce the computational, storage, and communications bottlenecks. We provide an overview of this emerging field, describe contemporary approximation techniqu ...
Institute of Electrical and Electronics Engineers2014
Mobility is often a central problem for people having muscle weaknesses. The need for new devices to assist walking and walk related activities is therefore growing. Lower limb actuated orthoses have already proven their positive impact with paraplegic pat ...
As many whole genomes are sequenced, comparative genomics is moving from pairwise comparisons to multiway comparisons framed within a phylogenetic tree. A central problem in this process is the inference of data for internal nodes of the tree from data giv ...
The reconstruction of a diffusion field, such as temperature, from samples collected by a sensor network is a classical inverse problem and it is known to be ill-conditioned. Previous work considered source models, such as sparse sources, to regularize the ...
Euclidean distance matrices (EDMs) are central players in many diverse fields including psychometrics, NMR spectroscopy, machine learning and sensor networks. However, they are not often exploited in signal processing. In this thesis, we analyze attributes ...
The determination of the optical flow is a central problem in image processing, as it allows to describe how an image changes over time by means of a numerical vector field. The estimation of the optical flow is however a very complex problem, which has be ...
In 1966, Graham showed that a simple procedure called list scheduling yields a 2-approximation algorithm for the central problem of scheduling precedence constrained jobs on identical machines to minimize makespan. To date this has remained the best algori ...
