Abstract— Network tomography infers internal network characteristics by sending and collecting probe packets from the network edge. Traditional tomographic techniques for general...
Minas Gjoka, Christina Fragouli, Pegah Sattari, At...
We present a noisy-OR Bayesian network model for simulation-based training, and an efficient search-based algorithm for automatic synthesis of plausible training scenarios from co...
Eugene Grois, William H. Hsu, Mikhail Voloshin, Da...
The first contribution of this paper is a probabilistic approach for measuring motion similarity for point sequences. While most motion segmentation algorithms are based on a rank...
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
We describe a very large scale distributed robotic system, involving a team of over 100 robots, that has been successfully deployed in large, unknown indoor environments, over ext...