A strategy for reconciling the information requirements of formal measurement uncertainty estimation principles with data generated from classical analytical method validation studies is described in detail. The approach involves a detailed analysis of influence factors on the analytical results, employing cause and effect analysis, followed by a formal reconciliation stage. The methodology is ...

We introduce the Redundant Information Neural Estimator (RINE), a method that allows efficient estimation for component of information about target variable is common to set sources, known as “redundant information”. show existing definitions redundant can be recast in terms an optimization over family functions. In contrast previous decompositions, which only evaluated discrete variables small...

Mutual Information (MI) and Conditional (CMI) are multi-purpose tools from information theory that able to naturally measure the statistical dependencies between random variables, thus they usually of central interest in several machine learning tasks, such as conditional independence testing representation learning. However, estimating CMI, or even MI, is infamously challenging due intractable...

We propose the use of Markov Logic Networks (MLNs) as a highly flexible and expressive formalism for the harmonic analysis of audio signals. Using MLNs information about the physical and semantic content of the signal can be intuitively and compactly encoded and expert knowledge can be easily expressed and combined using a single unified formal model that combines probabilities and logic. In pa...

Function point is the most widely used functional size measure in the software industry. It serves several purposes like software cost estimation, productivity management, quality management, benchmarking, outsourcing management, and several others. The goal of project FP-Formal, a research project funded by Bell Canada, is to formalize the function point measure in order to automate its calcul...