Motivated by realistic sensor network scenarios that have mis-informed nodes and variable network topologies, we propose a fundamentally different approach to routing that combine...
Christopher L. Barrett, Stephan Eidenbenz, Lukas K...
We study the problem of providing a sensor with an accurate estimate of the time, from a novel perspective which is complementary to the well-studied clock synchronization problem....
We demonstrate a system built using probabilistic techniques that allows for remarkably accurate localization across our entire office building using nothing more than the built-...
Andreas Haeberlen, Eliot Flannery, Andrew M. Ladd,...
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...