BayesPiles: Visualisation Support for Bayesian Network Structure Learning (2018)
Journal Article
Vogogias, A., Kennedy, J., Archambault, D., Bach, B., Smith, V. A., & Currant, H. (2018). BayesPiles: Visualisation Support for Bayesian Network Structure Learning. ACM transactions on intelligent systems and technology, 10(1), Article 5. https://doi.org/10.1145/3230623

We address the problem of exploring, combining and comparing large collections of scored, directed networks for understanding inferred Bayesian networks used in biology. In this feld, heuristic algorithms explore the space of possible network solutio... Read More about BayesPiles: Visualisation Support for Bayesian Network Structure Learning.

On the comparison of initialisation strategies in differential evolution for large scale optimisation (2017)
Journal Article
Segredo, E., Paechter, B., Segura, C., & González-Vila, C. I. (2018). On the comparison of initialisation strategies in differential evolution for large scale optimisation. Optimization Letters, 12(1), 221-234. https://doi.org/10.1007/s11590-017-1107-z

Differential Evolution (DE) has shown to be a promising global opimisation solver for continuous problems, even for those with a large dimensionality. Different previous works have studied the effects that a population initialisation strategy has on... Read More about On the comparison of initialisation strategies in differential evolution for large scale optimisation.

On the procedure for the series solution of second-order homogeneous linear differential equation via the complex integration method (2014)
Journal Article
Robin, W. (2014). On the procedure for the series solution of second-order homogeneous linear differential equation via the complex integration method. Nonlinear Analysis and Differential Equations, 2(4), 173-188. https://doi.org/10.12988/nade.2014.4713

The theory of series solutions for second-order linear homogeneous ordinary differential equation is developed ab initio, using an elementary complex integral expression (based on Herrera’ work [3]) derived and applied in previous papers [8, 9]. As w... Read More about On the procedure for the series solution of second-order homogeneous linear differential equation via the complex integration method.

Combined vs. Separate Views in Matrix-based Graph Analysis and Comparison. (2011)
Presentation / Conference Contribution
Melville, A., Graham, M., & Kennedy, J. (2011, July). Combined vs. Separate Views in Matrix-based Graph Analysis and Comparison. Presented at 15th International Conference Information Visualisation

While much work has been done in the area of visualization for analysis of graphs, relatively little research exists into how best to use visualization for comparing graphs. We have developed a suite of general graph comparison questions that can be... Read More about Combined vs. Separate Views in Matrix-based Graph Analysis and Comparison..

Combining FCA software and Sage. (2010)
Presentation / Conference Contribution
Priss, U. (2010, October). Combining FCA software and Sage. Presented at International Conference on Concept Lattices and Their Applications

Parallelization of the nearest-neighbour search and the cross-validation error evaluation for the kernel weighted k-nn algorithm applied to large data dets in matlab (2009)
Presentation / Conference Contribution
Rubio, G., Guillen, A., Pomares, H., Rojas, I., Paechter, B., Glosekotter, P., & Torres-Ceballos, C. I. (2009, June). Parallelization of the nearest-neighbour search and the cross-validation error evaluation for the kernel weighted k-nn algorithm applied to large data dets in matlab. Presented at 2009 International Conference on High Performance Computing & Simulation

The kernel weighted k-nearest neighbours (KWKNN) algorithm is an efficient kernel regression method that achieves competitive results with lower computational complexity than Least-Squares Support Vector Machines and Gaussian Processes. This paper pr... Read More about Parallelization of the nearest-neighbour search and the cross-validation error evaluation for the kernel weighted k-nn algorithm applied to large data dets in matlab.

Finding feasible timetables using group-based operators. (2007)
Journal Article
Lewis, R. M. R., & Paechter, B. (2007). Finding feasible timetables using group-based operators. IEEE Transactions on Evolutionary Computation, 11, 397-413. https://doi.org/10.1109/TEVC.2006.885162

This paper describes the applicability of the so-called "grouping genetic algorithm" to a well-known version of the university course timetabling problem. We note that there are, in fact, various scaling up issues surrounding this sort of algorithm a... Read More about Finding feasible timetables using group-based operators..

FCA interpretation of relation algebra. (2006)
Presentation / Conference Contribution
Priss, U. (2006, February). FCA interpretation of relation algebra. Presented at 4th International Conference on Formal Concept Analysis

This paper discusses an interpretation of relation algebra and fork algebra with respect to FCA contexts. In this case, "relation algebra" refers to the DeMorgan-Peirce-Schroeder-Tarski algebra and not to the "relational algebra" as described by Codd... Read More about FCA interpretation of relation algebra..

Hyper-heuristics. (2005)
Book Chapter
Ross, P. (2005). Hyper-heuristics. In E. Burke, & G. Kendall (Eds.), Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques (529-556). Springer-Verlag

This chapter introduces and overviews an emerging methodology in search and optimisation. One of the key aims of these new approaches, which have been termed hyper-heuristics, is to raise the level of generality at which optimisation systems can oper... Read More about Hyper-heuristics..

Using ERMIA for the Evaluation of a Theorem Prover Interface (2004)
Presentation / Conference Contribution
Jackson, M., Benyon, D., & Lowe, H. Using ERMIA for the Evaluation of a Theorem Prover Interface

ERMIA (Entity-Relationship Modelling of Information Artefacts) provides an extension to entity-relationship
modelling techniques to provide a structural representation of the interaction between people and “information
artefacts”. Such a representa... Read More about Using ERMIA for the Evaluation of a Theorem Prover Interface.

Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics. (2003)
Presentation / Conference Contribution
Ross, P., Marin-Blazquez, J. G., Schulenburg, S., & Hart, E. (2003, July). Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics. Presented at Genetic and Evolutionary Computation Conference (GECCO) 2003

The idea underlying hyper-heuristics is to discover some
combination of familiar, straightforward heuristics that performs very well across a whole range of problems. To be worthwhile, such a combination should outperform all of the constituent heur... Read More about Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics..

Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. (2002)
Presentation / Conference Contribution
Ross, P., Schulenburg, S., Marin-Blazquez, J. G., & Hart, E. (2002, July). Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. Presented at Genetic and Evolutionary Computation Conference (GECCO)

Evolutionary algorithms (EAs) often appear to be a ‘black box’, neither offering worst-case bounds nor any guarantee of optimality when used to solve individual problems. They can also take much longer than non-evolutionary methods. We
try to addres... Read More about Hyper-heuristics: learning to combine simple heuristics in bin-packing problems..

Design rational for semi-automated theorem provers. (1998)
Journal Article
Lowe, H., Jackson, M., & Benyon, D. (1998). Design rational for semi-automated theorem provers. Formal Aspects of Computing,

Machine independent algorithm for concurrent finite-element problems (1996)
Presentation / Conference Contribution
Buchanan, W. J., & Gupta, N. K. (1996, April). Machine independent algorithm for concurrent finite-element problems. Presented at 3rd International Conference on Computation in Electromagnetics (CEM 96)

The finite-element method, initially developed for mechanical and civil engineering applications, is now applied to electromagnetics. This paper describes how parallel processing applies to finite-element simulations. The methods discussed are the pa... Read More about Machine independent algorithm for concurrent finite-element problems.