Updating Credal Networks is Approximable in Polynomial Time

Credal networks relax the precise probability requirement of Bayesian networks, enabling a richer representation of uncertainty in the form of closed convex sets of probability measures. The increase in expressiveness comes at the expense of higher computational costs. In this paper, we present a new variable elimination algorithm for exactly computing posterior inferences in extensively specified credal networks, which is empirically shown to outperform a state-of-the-art algorithm. The algorithm is then turned into a provably good approximation scheme, that is, a procedure that for any input is guaranteed to return a solution not worse than the optimum by a given factor. Remarkably, we show that when the networks have bounded treewidth and bounded number of states per variable the approximation algorithm runs in time polynomial in the input size and in the inverse of the error factor, thus being the first known fully polynomial-time approximation scheme for inference in credal networks.

Neural networks PID autotuning with real-time adaptation

Despite the developments in more sophisticated controllers, still the Proportional, Integral and Derivative (PID) controller is by far the controller most widely used in industry automation.

BitTorrent based transmission of real-time scalable video over P2P networks

The number of software applications available on the Internet for distributing video streams in real time over P2P networks has grown quickly in the last two years. Typical this kind of distribution is made by television channel broadcasters which try to make their content globally available, using viewer's resources to support a large scale distribution of video without incurring in incremental costs. However, the lack of adaptation in video quality, combined with the lack of a standard protocol for this kind of multimedia distribution has driven content providers to basically ignore it as a solution for video delivery over the Internet. While the scalable extension of the H. 264 encoding (H.264/SVC) can be used to support terminal and network heterogeneity, it is not clear how it can be integrated in a P2P overlay to form a large scale and real time distribution. In this paper, we start by defining a solution that combines the most popular P2P file-sharing protocol, the BitTorrent, with the H. 264/SVC encoding for a real-time video content delivery. Using this solution we then evaluate the effect of several parameters in the quality received by peers.