Abstract. Phylogeny reconstruction from molecular data poses complex optimization problems: almost all optimization models are NP-hard and thus computationally intractable. Yet app...
This paper exploits recent developments in sparse approximation and compressive sensing to efficiently perform localization in a sensor network. We introduce a Bayesian framework...
Volkan Cevher, Petros Boufounos, Richard G. Barani...
Abstract. This paper is concerned with a method for computing reachable sets of linear continuous systems with uncertain input. Such a method is required for verification of hybrid...
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Uncertain data streams are increasingly common in real-world deployments and monitoring applications require the evaluation of complex queries on such streams. In this paper, we c...
Thanh T. L. Tran, Andrew McGregor, Yanlei Diao, Li...