Conformal Prediction is a recently developed framework for reliable confident predictions. In this work we discuss its possible application to big data coming from different, possibly heterogeneous data sources. On example of anomaly detection problem, we study the question of saving validity of Conformal Prediction in this case. We show that the straight forward averaging…

The concept of cloud computing has arisen thanks to academic work in the fields of utility computing, distributed computing, virtualisation, and web services. By using cloud computing, which can be accessed from anywhere, newly-launched businesses can minimise their start-up costs. Among the most important notions when it comes to the construction of cloud computing is…

Over the last decades, numerous distributed consensus-based algorithms have found a wide application as a complementary mechanism for data aggregation in wireless sensor networks. In this paper, we provide an analysis of the generalized Metropolis-Hastings algorithm for data aggregation with a fully-distributed stopping criterion. The goal of the implemented stopping criterion is to effectively bound…