We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
We investigate the topical structure of the set of documents used to expand a query in pseudorelevance feedback (PRF). We propose a coherence score to measure the relative topical...
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
This paper presents SHiMmer, a wireless platform for sensing and actuation that combines localized processing with energy harvesting to provide long-lived structural health monito...
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...