A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
The aim of query-based sampling is to obtain a sufficient, representative sample of an underlying (text) collection. Current measures for assessing sample quality are too coarse gr...
In this work, we develop a novel mathematical model to analyze di erent location update protocols for mobile cellular network. Our model can capture many important features of use...
Consensus is one of the most fundamental problems in fault-tolerant distributed computing. This paper proposes a mechanical method for analyzing the condition that allows one to s...
We describe and evaluate a multi-objective optimisation (MOO) algorithm that works within the Probability Collectives (PC) optimisation framework. PC is an alternative approach to ...