Computationally Efficient Multiple-Independent-Gate Device Model

Computationally Efficient Convolved Multiple Output Gaussian Processes

Recently there has been an increasing interest in regression methods that deal with multiple outputs. This has been motivated partly by frameworks like multitask learning, multisensor networks or structured output data. From a Gaussian processes perspective, the problem reduces to specifying an appropriate covariance function that, whilst being positive semi-definite, captures the dependencies ...

Computationally and Statistically Efficient Model Fitting Techniques

In large-scale stochastic simulations, analysis with sufficient accuracy is often extremely time consuming. The complexity of the analysis is exacerbated with increasing dimensionality of the parameter space and sudden abruptness in the topology of the input-output response surface. This paper addresses computational issues in fitting and generating error measures of simulation metamodels, demo...

A computationally efficient multipitch analysis model

A computationally efficient model for multipitch and periodicity analysis of complex audio signals is presented. The model essentially divides the signal into two channels, below and above 1000 Hz, computes a “generalized” autocorrelation of the low-channel signal and of the envelope of the high-channel signal, and sums the autocorrelation functions. The summary autocorrelation function (SACF) ...

Multiple Objective Evolutionary Algorithms for Independent, Computationally Expensive Objective Evaluations

Reference Resource - Efficient Measurement - Device - Independent Entanglement

Imperfections in experimental measurement schemes can lead to falsely identifying, or over estimating, entanglement in a quantum system. A recent solution to this is to define schemes that are robust to measurement imperfections measurement device independent entanglement witness (MDI-EW). Here we introduce a novel approach for MDI-EW, which significantly reduces the experimental complexity and...