We show that finding small solutions to random modular linear equations is at least as hard as approximating several lattice problems in the worst case within a factor almost line...
Abstract-- In this paper we study different distributed estimation schemes for stochastic discrete time linear systems where the communication between the sensors and the estimatio...
We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of t...
In this paper the performance of OVSF and NOVSF codes in WCDMA are evaluated by calculating their blocking probability and plotting graphs between blocking probability and new call...
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...