Now showing items 21-25 of 25
Nearly-optimal scheduling of users with Markovian time-varying transmission rates
We address the problem of developing a well-performing and implementable scheduler of users with wireless connections to the central controller, which arise in areas such as mobile data networks, heterogeneous networks, ...
Efficient approximation of probability distributions with k-order decomposable models
During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models. Some of these algorithms can be used to search for a maximum likelihood decomposable ...
Fitting the data from embryo implantation prediction: Learning from label proportions
Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve ...
Joint topology optimization, power control and spectrum allocation for intra-vehicular multi-hop sensor networks using dandelion-encoded heuristics
In the last years the interest in multi-hop communications has gained momentum within the research community due to the challenging characteristics of the intra-vehicular radio environment and the stringent robustness ...
The Role of Local Urban Traffic and Meteorological Conditions in Air Pollution: A Data-based Case Study in Madrid, Spainc
Urban air pollution is a matter of growing concern for both public adminis- trations and citizens. Road traffic is one of the main sources of air pollutants, though topography characteristics and meteorological conditions ...