Context. Understanding the intricacies behind presence and absence of sources in an astronomical catalogue is crucial for accurate interpretation data. In particular, multi-dimensional Gaia data, filters cuts on different parameters or measurements introduce a selection function that may unintentionally alter scientific conclusions subtle ways. Aims. We aim to develop methodology estimate subsa...

Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of the main challenges in scaling RL to real-world applications. Here we consider the Gaussian process based framework GPTD for approximate policy evaluation, and propose feature selection through marginal likelihood optimization of...

Adaptive routing algorithms, which dynamically select the route of a packet, have been widely studied for interconnection networks in massively parallel computers. An output selection function (OSF), which decides the output channel when some legal channels are free, is essential for an adaptive routing. In this paper, we propose a simple and efficient OSF called minimal multiplexed and least-r...

In this paper, a new method for developing a lower bound on exact completion time distribution function of stochastic PERT networks is provided that is based on simplifying the structure of this type of network. The designed mechanism simplifies network structure by arc duplication so that network distribution function can be calculated only with convolution and multiplication. The selection of...

In this paper, a new method for developing a lower bound on exact completion time distribution function of stochastic PERT networks is provided that is based on simplifying the structure of this type of network. The designed mechanism simplifies network structure by arc duplication so that network distribution function can be calculated only with convolution and multiplication. The selection of...