This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
From the World Wide Web to supply chains and scientific simulations, distributed systems are a widely used and important approach to building computational systems. Tracking prov...
The proliferation of linked data on the Web paves the way to a new generation of applications that exploit heterogeneous data from different sources. However, because this Web of d...
Emerging ubiquitous and pervasive computing applications often need to know where things are physically located. To meet this need, many locationsensing systems have been develope...