This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
This paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackers' motion...
Data-intensive applications are increasingly designed to execute on large computing clusters. Grouped aggregation is a core primitive of many distributed programming models, and i...
— In this paper, we present a distributed algorithm for detecting redundancies in a sensor network with no location information. We demonstrate how, in the absence of localizatio...
— We present a distributed scheduling algorithm for provisioning of guaranteed link bandwidths in ad hoc mesh networks. The guaranteed link bandwidths are necessary to provide de...