Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Join techniques deploying approximate match predicates are fundamental data cleaning operations. A variety of predicates have been utilized to quantify approximate match in such o...
Sudipto Guha, Nick Koudas, Divesh Srivastava, Xiao...
Accurate and efficient integration of geospatial data is an important problem with applications in areas such as emergency response and urban planning. Some of the key challenges ...
We present an image-based Simultaneous Localization and Mapping (SLAM) framework with online, appearanceonly loop closing. We adopt a layered approach with metric maps over small ...
— The dynamic nature of mobile ad hoc networks poses fundamental challenges to the design of service composition schemes that can minimize the effect of service disruptions. Alth...