Many problems in vision can be formulated as Bayesian inference. It is important to determine the accuracy of these inferences and how they depend on the problem domain. In recent...
Alan L. Yuille, James M. Coughlan, Song Chun Zhu, ...
— We define and study the scheduling complexity in wireless networks, which expresses the theoretically achievable efficiency of MAC layer protocols. Given a set of communicati...
— This paper focuses on the problem of rostering in intermittently connected passive RFID networks. It aims to report a list of tagged mobile nodes that appear in given intereste...
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
The element connectivity problem falls in the category of survivable network design problems { it is intermediate to the versions that ask for edge-disjoint and vertex-disjoint pa...
Kamal Jain, Ion I. Mandoiu, Vijay V. Vazirani, Dav...