Sæmundur Ó. Haraldsson
Alexander Brownlee
John R. Woodward
Markus Wagner
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Digital Library
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- S.O. Haraldsson, 2017. 'Genetic Improvement of Software: From Program Landscapes to the Automatic Improvement of a Live System', PhD thesis, University of Stirling, Stirling. http://hdl.handle.net/1893/26007Google Scholar
- S.O. Haraldsson, John R. Woodward, Alexander E. I. Brownlee, Albert V. Smith, and Vilmundur Gudnason. 2017. Genetic improvement of runtime and its fitness landscape in a bioinformatics application. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '17). ACM, New York, NY, USA, 1521--1528. Google ScholarDigital Library
- S.O. Haraldsson, 2017. 'Genetic Improvement of Software: From Program Landscapes to the Automatic Improvement of a Live System', PhD thesis, University of Stirling, Stirling. http://hdl.handle.net/1893/26007Google Scholar
- S. O. Haraldsson, R. D. Brynjolfsdottir, J. R. Woodward, K. Siggeirsdottir and V. Gudnason, "The use of predictive models in dynamic treatment planning," 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, 2017, pp. 242--247. Google ScholarCross Ref
- S. O. Haraldsson, R. D. Brynjolfsdottir, V. Gudnason, K. Tomasson and K. Siggeirsdottir, "Predicting changes in quality of life for patients in vocational rehabilitation," 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), Rhodes, 2018, pp. 1--8. Google ScholarCross Ref
- Siggeirsdottir, K., Brynjolfsdottir, R.D., Haraldsson, S.O., Vidar, S., Gudmundsson, E.G., Brynjolfsson, J.H., Jonsson, H., Hjaltason, O. and Gudnason, V., 2016. Determinants of outcome of vocational rehabilitation. Work, 55(3), pp.577--583. Google ScholarCross Ref
- J. Petke, B. Alexander, E.T. Barr. A.E.I. Brownlee, M. Wagner, and D.R. White, 2019. 'A survey of genetic improvement search spaces'. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '19). ACM, New York, NY, USA, 1715--1721. Google ScholarDigital Library
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- M.A. Bokhari, B. Alexander, and M. Wagner, 2019. 'In-vivo and offline optimisation of energy use in the presence of small energy signals: A case study on a popular Android library'. In Proceedings of the EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous'18), ACM, New York, NY, USA, 207--215. Google ScholarDigital Library
- M.A. Bokhari, B. Alexander, and M. Wagner, 2020. 'Towards Rigorous Validation of Energy Optimisation Experiments'. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '20). ACM, New York, NY, USA. URL: https://arxiv.org/abs/2004.04500v1Google Scholar
- M.A. Bokhari, B.R. Bruce, B. Alexander, and M. Wagner, 2017. 'Deep parameter optimisation on Android smartphones for energy minimisation: a tale of woe and a proof-of-concept'. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '17). ACM, New York, NY, USA, 1501--1508. URL: ttps:// Google ScholarDigital Library
- M.A. Bokhari, L. Weng, M. Wagner, and B. Alexander, 2019. 'Mind the gap - a distributed framework for enabling energy optimisation on modern smart-phones in the presence of noise, drift, and statistical insignificance'. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC '19). IEEE, 1330--1337. Google ScholarDigital Library
- A. Agrawal, T. Menzies, L. Minku, M. Wagner, and Z. Yu, 2020. 'Better software analytics via "DUO": Data mining algorithms using/used-by optimizers'. Empirical Software Engineering, Springer. Published 22 April 2020. Google ScholarDigital Library
- V. Nair, A. Agrawal, J. Chen, W. Fu, G. Mathew, T. Menzies, L. Minku, M. Wagner, and Z. Yu, 2018. 'Data-driven search-based software engineering'. In Proceedings of the International Conference on Mining Software Repositories (MSR'18), ACM, New York, NY, USA, 341--352. Google ScholarDigital Library
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