This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
We consider a multi-agent optimization problem where agents aim to cooperatively minimize a sum of local objective functions subject to a global inequality constraint and a global ...
We briefly present the current state-of-the-art approaches for group and extended object tracking with an emphasis on particle methods which have high potential to handle complex...
—In many application scenarios sensors need to calculate the average of some local values, e.g. of local measurements. A possible solution is to rely on consensus algorithms. In ...
Konstantin Avrachenkov, Mahmoud El Chamie, Giovann...
— We consider the uplink power control problem where mobile users in different cells are communicating with their base stations. We formulate the power control problem as the min...
Sundhar Srinivasan Ram, Venugopal V. Veeravalli, A...