Analysis and Design of Large Multi-Agent Swarms Through Continuum Approximations Self-organization is a pervasive phenomenon in nature, which has inspired the development of multi-robot systems that can mimic their biological counterparts. As we consider larger groups of robotic swarms, new theoretical challenges appear that are…

Scale Mixture Modeling of Priors for Sparse Signal Recovery This talk will discuss Bayesian approaches to solving the sparse signal recovery problem. In particular, methods based on priors that admit a scale mixture representation will be discussed with emphasis on Gaussian scale mixture modeling. In the context of MAP estimation…