The CUR decomposition provides an approximation of a matrix X that has low reconstruction error and that is sparse in the sense that the resulting approximation lies in the span o...
Training of conditional random fields often takes the form of a double-loop procedure with message-passing inference in the inner loop. This can be very expensive, as the need to...
This work deals with trajectory optimization for a network of robotic sensors sampling a spatio-temporal random field. We examine the problem of minimizing over the space of networ...
This paper presents a rigorous analytic study of gossip-based message dissemination schemes that can be employed for content/service dissemination or discovery in unstructured and...
Siyu Tang, Eva Jaho, Ioannis Stavrakakis, Ioannis ...
—We address the problem of estimating a random vector X from two sets of measurements Y and Z, such that the estimator is linear in Y . We show that the partially linear minimum ...