Motivated by applications to sensor, peer-to-peer, and adhoc networks, we study the problem of computing functions of values at the nodes in a network in a totally distributed man...
In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-differe...
Alessandro Lazaric, Mohammad Ghavamzadeh, Ré...
Abstract. For many statistical pattern recognition methods, distributions of sample vectors are assumed to be normal, and the quadratic discriminant function derived from the proba...
Uncertainty processing methods are analysed from the viewpoint of their sensitivity to small variations of certainty factors. The analysis makes use of the algebraic theory which ...
We consider two-stage pure integer programs with discretely distributed stochastic right-hand sides. We present an equivalent superadditive dual formulation that uses the value fun...