Robots must complete their tasks in spite of unreliable actuators and limited, noisy sensing. In this paper, we consider the information requirements of such tasks. What sensing a...
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
Causal reasoning is primarily concerned with what would happen to a system under external interventions. In particular, we are often interested in predicting the probability distr...
Much of the literature on symmetry reductions for model checking assumes a simple model of computation where the local state of each component in a concurrent system can be repres...
We combine space-time coding and transmit beamforming over multiple-antenna quasi-static fading channels using resolution-constrained channel state information at the transmitter ...