All Outputs (9)

Analyst-driven XAI for time series forecasting: Analytics for telecoms maintenance (2024)
Conference Proceeding
Barrett, J., Legg, P., Smith, J., & Boyle, C. (in press). Analyst-driven XAI for time series forecasting: Analytics for telecoms maintenance.

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.

A decision-making architecture for human-robot collaboration: Model transferability (2023)
Conference Proceeding
Sobhani, M., Smith, J., Pipe, A., & Peer, A. (2023). A decision-making architecture for human-robot collaboration: Model transferability. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1 (719-726). https://doi.org/10.5220/0012210600003543

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.

Statistical disclosure controls for machine learning models (2021)
Conference Proceeding
Krueger, S., Mansouri-Benssassi, E., Ritchie, F., & Smith, J. (2021). Statistical disclosure controls for machine learning models

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.

Using active learning to understand the videoconference experience: A case study (2020)
Conference Proceeding
Llewellyn, S., Simons, C., & Smith, J. (2020). Using active learning to understand the videoconference experience: A case study. https://doi.org/10.1007/978-3-030-63799-6_30

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.

The Baldwin effect hinders self-adaptation (2014)
Conference Proceeding
Smith, J. (2014). The Baldwin effect hinders self-adaptation. In J. Branke, B. Filipic, J. Smith, & T. Bartz-Beielstein (Eds.), Parallel Problem Solving from Nature – PPSN XIII. , (120-129). https://doi.org/10.1007/978-3-319-10762-2_12

The “end-game” of evolutionary optimisation is often largely governed by the efficiency and effectiveness of searching regions of space known to contain high quality solutions. In a traditional EA this role is done via mutation, which creates a tensi... Read More about The Baldwin effect hinders self-adaptation.

Aspect oriented software fault tolerance and analytically redundant design framework (2010)
Conference Proceeding
Hameed, K., Williams, R., & Smith, J. (2010). Aspect oriented software fault tolerance and analytically redundant design framework. In 2010 International Conference on Dependable Systems and Networks Workshops (DSN-W) (38-44). https://doi.org/10.1109/DSNW.2010.5542623

Diversity or redundancy based software fault tolerance does not come for free; rather it introduces additional complexity to the core functionality in the form of redundancy development, management and controlled execution. This results in tangling o... Read More about Aspect oriented software fault tolerance and analytically redundant design framework.

Pre-processing optimisation applied to the classical integer programming model for statistical disclosure control (2008)
Conference Proceeding
Staggemeier, A., Serpell, M., Clark, A., & Smith, J. (2008). Pre-processing optimisation applied to the classical integer programming model for statistical disclosure control. . https://doi.org/10.1007/978-3-540-87471-3_3

A pre-processing optimisation is proposed that can be applied to the integer and mixed integer linear programming models that are used to solve the cell suppression problem in statistical disclosure control. In this paper we report our initial findin... Read More about Pre-processing optimisation applied to the classical integer programming model for statistical disclosure control.

Gene libraries: Coverage, efficiency and diversity (2006)
Conference Proceeding
Cayzer, S., & Smith, J. (2006). Gene libraries: Coverage, efficiency and diversity. In H. Bersini, & J. Carneiro (Eds.), In Artificial Immune Systems. ICARIS 2006. , (136-149). https://doi.org/10.1007/11823940_11

Gene libraries are a biological mechanism for generating combinatorial diversity in the immune system. However, they also bias the antibody creation process, so that they can be viewed as a way of guiding lifetime learning mechanisms. In this paper w... Read More about Gene libraries: Coverage, efficiency and diversity.

Co-evolving memetic algorithms: Initial investigations (2002)
Conference Proceeding
Smith, J. (2002). Co-evolving memetic algorithms: Initial investigations. In J. J. M. Guervós, P. Adamidis, H. Beyer, H. Schwefel, & J. Fernández-Villacañas (Eds.), In Parallel Problem Solving from Nature — PPSN VII (537-546). https://doi.org/10.1007/3-540-45712-7_52

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.