All Outputs (136)

Study of fitness landscapes for the HP model of protein structure prediction
Presentation / Conference Contribution

Co-evolving memetic algorithms: A learning approach to robust scalable optimisation
Presentation / Conference Contribution

Parameter perturbation mechanisms in binary coded gas with self-adaptive mutation
Presentation / Conference Contribution

Co-evolving memetic algorithms: Initial investigations
Presentation / Conference Contribution

This paper presents and examines the behaviour of a system whereby the rules governing local search within a Memetic Algorithm are co-evolved alongside the problem representation. We describe the rationale for such a system, and the implementation of... Read More about Co-evolving memetic algorithms: Initial investigations.

An alternative approach for the evaluation of the neocognitron
Presentation / Conference Contribution

Emergence of profitable search strategies based on a simple inheritance mechanism
Presentation / Conference Contribution

New methods for tunable, random landscapes
Presentation / Conference Contribution

Genetic selection of features for clustering and classification
Presentation / Conference Contribution

Adaptively parameterised evolutionary systems: Self adaptive recombination and mutation in a genetic algorithm
Presentation / Conference Contribution

An adaptive poly-parental recombination strategy
Presentation / Conference Contribution

Genetic feature selection for clustering and classification
Presentation / Conference Contribution

A modified neocognitron network for medical signal classification
Presentation / Conference Contribution

Using active learning to understand the videoconference experience: A case study
Presentation / Conference Contribution

Videoconferencing is becoming ubiquitous, especially so during the COVID-19 pandemic. However, user experience of a videoconference call can be variable. To better understand and classify the performance of videoconference call systems, this paper re... Read More about Using active learning to understand the videoconference experience: A case study.

Statistical disclosure controls for machine learning models
Presentation / Conference Contribution

Artificial Intelligence (AI) models are trained on large datasets. Where the training data is sensitive, the data holders need to consider risks posed by access to the training data and risks posed by the models that are released. The first problem c... Read More about Statistical disclosure controls for machine learning models.

A decision-making architecture for human-robot collaboration: Model transferability
Presentation / Conference Contribution

In this paper, we aim to demonstrate the potential for wider-ranging capabilities and ease of transferability of our recently developed decision-making architecture for human-robot collaboration. To this end, a somewhat related but different applicat... Read More about A decision-making architecture for human-robot collaboration: Model transferability.

Analyst-driven XAI for time series forecasting: Analytics for telecoms maintenance
Presentation / Conference Contribution

Time series forecasting facilitates real-time anomaly detection in telecom networks, predicting events that disrupt security and service. Current research efforts have been found to focus on new forecasting libraries, more rigorous data cleaning meth... Read More about Analyst-driven XAI for time series forecasting: Analytics for telecoms maintenance.