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  • Chapter

    A basis function approach to Bayesian inference in diffusion processes

    Shen, Y., Cornford, D. & Opper, M., 2009, IEEE/SP 15th Workshop on Statistical Signal Processing, 2009. SSP '09. IEEE, p. 365-368 4 p.

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  • A data structure for improved gp analysis via efficient computation and visualisation of population measures

    Ekárt, A. & Gustafson, S., 1 Jan 2004, Genetic programming: 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings. Keijzer, M., O’Reilly, U-M., Lucas, S., Costa, E. & Soule, T. (eds.). Berlin (DE): Springer, p. 35-46 12 p. (Lecture Notes in Computer Science ; vol. 3003).

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  • Analysing time series structure with hidden Markov models

    Azzouzi, M. & Nabney, I. T., 2 Sept 1998, Proceedings of the 1998 IEEE Signal Processing Society Workshop, Neural Networks for Signal Processing VIII, 1998. Constantinides, T., Kung, S. Y., Niranjan, M. & Wilson, E. (eds.). Cambridge, UK: IEEE, Vol. 8. p. 402-408 7 p. (Proceedings of the 1998 IEEE Signal Processing Society Workshop).

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  • An End-to-End Scalable Iterative Sequence Tagging with Multi-Task Learning

    Gui, L., Du, J., Zhao, Z., He, Y., Xu, R. & Fan, C., 14 Aug 2018, (E-pub ahead of print) CCF International Conference on Natural Language Processing and Chinese Computing. Springer, Vol. 11109. p. 288-298 (Natural Language Processing and Chinese Computing; vol. 11109).

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  • Architectures for collective self-aware computing systems

    Diaconescu, A., Bellman, K. L., Esterle, L., Giese, H., Götz, S., Lewis, P. & Zisman, A., 21 Feb 2017, Self-Aware Computing Systems. Springer, p. 191-235 45 p.

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  • Assessing self-awareness

    Esterle, L., Bellman, K. L., Becker, S., Koziolek, A., Landauer, C. & Lewis, P., 21 Feb 2017, Self-Aware Computing Systems. Springer, p. 465-481 17 p.

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  • AWESSOME: An Unsupervised Sentiment Intensity Scoring Framework Using Neural Word Embeddings

    Htait, A. & Azzopardi, L., 30 Mar 2021, European Conference on Information Retrieval: Advances in Information Retrieval. Springer, p. 509-513 5 p. (Lecture Notes in Computer Science (LNCS)).

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  • CADS*: Computer-Aided Development of self-* systems

    Calinescu, R. C. & Kwiatkowska, M. Z., 28 Mar 2009, Fundamental Approaches to Software Engineering. Berlin (DE): Springer, Vol. 5503. p. 421-424 4 p. (Lecture Notes in Computer Science; vol. 5503).

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  • Combining the wavelet transform and forecasting models to predict gas forward prices

    Nguyen, H. T. & Nabney, I. T., 11 Dec 2008, Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08. IEEE, p. 311-317 7 p.

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  • Computational methods and tools for decision support in biomedicine: an overview of algorithmic challenges

    Dimou, I. N., Zervakis, M. E., Lowe, D. & Tsiknakis, M., Apr 2009, Handbook of research on advanced techniques in diagnostic imaging and biomedical applications. Exarchos, T. P., Papadopoulos, A. & Fotiadis, D. I. (eds.). IGI Global, p. 1-17 17 p.

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  • Computational self-awareness and learning machines

    Lewis, P. R., 2014, The Computer After Me: Awareness and Self-Awareness in Autonomic Systems. World Scientific, p. 267-280 14 p.

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  • CONNECT challenges: towards emergent connectors for eternal networked systems

    Issarny, V., Steffen, B., Jonsson, B., Blair, G., Grace, P., Kwiatowska, M., Calinescu, R. C., Inverardi, P., Tivoli, M., Bertolino, A. & Sabetta, A., 2 Jun 2009, 2009 14th IEEE International Conference on Engineering of Complex Computer Systems. Postdam, Germany: IEEE, p. 154-161 8 p.

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  • Dynamic variability in adaptive systems

    Chitchyan, R., Morin, B., Fleurey, F., Bencomo, N., Solberg, A. & Genssler, T., 2011, Aspect-oriented, model-driven software product lines: the AMPLE way. Rashid, A., Royer, J-C. & Rummler, A. (eds.). Cambridge University Press, p. 347-377 31 p.

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  • Early risk detection of self-harm using BERT-based transformers

    Martínez-Castaño, R., Htait, A., Azzopardi, L. & Moshfeghi, Y., 15 Sept 2022, Early Detection of Mental Health Disorders by Social Media Monitoring: The First Five Years of the eRisk Project. Crestani, F., Losada, D. E. & Parapar, J. (eds.). p. 183-206 (Studies in Computational Intelligence; vol. 1018).

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  • e-CAF: flexible marking schemes for electronic coursework assessment and feedback

    Wong, S. H. S., Sellers, A. J. & Beaumont, A. J., 2008, Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008. Chesapeake, VA (US): AACE, p. 2289-2297 9 p.

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  • Energy forward price prediction with a hybrid adaptive model

    Nguyen, H. T. & Nabney, I. T., 30 Mar 2009, IEEE Symposium on Computational Intelligence for Financial Engineering, 2009. CIFEr '09. IEEE, p. 66-71 6 p.

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  • Energy harvest: A possible solution to the open field stubble burning in Punjab, India

    Sagi, S., Patel, A. R., Berry, R. F. & Singh, H., 1 Jan 2015, Biomass and Biofuels: Advanced Biorefineries for Sustainable Production and Distribution. Jose, S. & Bhaskar, T. (eds.). Taylor & Francis, p. 183-197 15 p.

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  • Establishing a framework for dynamic risk management in 'intelligent' aero-engine control

    Kurd, Z., Kelly, T., McDermid, J. A., Calinescu, R. C. & Kwiatkowska, M. Z., 3 Sept 2009, Computer Safety, Reliability, and Security 28th International Conference, SAFECOMP 2009, Hamburg, Germany, September 15-18, 2009. Proceedings. Berlin (DE): Springer, Vol. 5775/2009. p. 326-341 16 p. (Lecture Notes in Computer Science).

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  • Evaluating the effectiveness of Bayesian feature selection

    Nabney, I. T., Evans, D. J., Brule, Y. & Gordon, C., 2005, Applications of probabilistic modelling in medical informatics and bioinformatics. Dybowski, R., Husmeier, D. & Roberts, S. J. (eds.). Springer, p. 371-389 19 p. (Advanced information and knowledge processing).

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  • Exchanging uncertainty: interoperable geostatistics?

    Williams, M., Cornford, D., Bastin, L. & Ingram, B. R., 2008, geoENV VII – Geostatistics for Environmental Applications. Springer, Vol. 16. p. 321-331 11 p.

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  • Face recognition and semantic features

    Zhou, H., Yuan, Y. & Shi, C., Dec 2009, Semantic mining technologies for multimedia databases. Tao, D., Xu, D. & Li, X. (eds.). IGI Global, p. 80-98 19 p.

    Research output: Chapter in Book/Published conference output › Chapter

  • Foreword: first workshop requirements@run.time

    Sawyer, P., Bencomo, N., Whittle, J., Berry, D. M. & Finkelstein, A., 2010, 2010 1st International Workshop on Requirements@Run.Time, RE@RunTime 2010. IEEE, p. i-ii 2 p.

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  • General-purpose autonomic computing

    Calinescu, R. C., 12 Jun 2009, Autonomic Computing and Networking. Denko, M. K., Yang, L. T. & Zhang, Y. (eds.). Springer, p. 3-30 28 p.

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  • Genie: supporting the model driven development of reflective, component-based adaptive systems

    Bencomo, N., Grace, P., Flores, C., Hughes, D. & Blair, G., 2008, Proceedings : ICSE '08 proceedings of the 30th international conference on software engineering . New York, NY (US): ACM, p. 811-814 4 p.

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  • GIS-based data synthesis and visualization

    Rocchini, D., Garzon-Lopez, C. X., Barbosa, A. M., Delucchi, L., Olandi, J. E., Marcantonio, M., Bastin, L. & Wegmann, M., 21 Oct 2017, Ecological Informatics: Data Management and Knowledge Discovery: Third Edition. Springer, p. 273-286 14 p.

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  • Implementation of a generic autonomic framework

    Calinescu, R. C., 16 Mar 2008, Proceedings of the 4th International Conference on Autonomic and Autonomous Systems. ICAS 2008. Greenwood, D. (ed.). IEEE, p. 124-129 6 p.

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  • Markets and clouds: Adaptive and resilient computational resource allocation inspired by economics

    Lewis, P. R., Faniyi, F., Bahsoon, R. & Yao, X., 23 Jun 2014, Adaptive, Dynamic, and Resilient Systems. Suri, N. & Cabri, G. (eds.). CRC Press, p. 285-318 34 p.

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  • Methodology for the model-driven development of self-managing systems

    Calinescu, R. C., May 2008, Proceedings of the 5th conference on Computing frontiers. New York (US): ACM, p. 115-116 2 p.

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  • Modelling conditional probability distributions for periodic variables

    Nabney, I. T., Bishop, C. M. & Legleye, C., 26 Jun 1995, Fourth International Conference on Artificial Neural Networks. IEEE, Vol. 4. p. 177-182 6 p.

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  • Modelling conditional probability distributions for periodic variables

    Nabney, I. T. & Bishop, C. M., 1995, Proceedings International Conference on Artificial Neural Networks ICANN'95. Fougelman-Soulie, F. & Gallinari, P. (eds.). Paris (FR): EC2 et Cie, Vol. 2. p. 209-214 6 p.

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  • Modelling financial time series with switching state space models

    Azzouzi, M. & Nabney, I. T., 1999, Proceedings of the IEEE/IAFE 1999 Conference on Computational Intelligence for Financial Engineering. Port Jefferson, NY: IEEE, p. 240-249 10 p.

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  • Online approximations for wind-field models

    Csató, L., Cornford, D. & Opper, M., 1 Jan 2001, Artificial Neural Networks — ICANN 2001. Springer, Vol. 2130. p. 300-307 8 p. (Lecture Notes in Computer Science).

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  • On the use of software models during software execution

    Bencomo, N., 2009, Proceedings of the 2009 31st International Conference on Software Engineering and ICSE Workshops. p. 62-67 6 p.

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  • Parallel geostatistics for sparse and dense datasets

    Ingram, B. R. & Cornford, D., 2008, geoENV VII – Geostatistics for Environmental Applications. Springer, Vol. 16. p. 371-381 11 p.

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  • Practical 3D reconstruction based on photometric stereo

    Vogiatzis, G. & Hernández, C., 2010, Computer vision: detection, recognition and reconstruction. Cipolla, R., Battiato, S. & Farinella, G. M. (eds.). Berlin (US): Springer, p. 313-345 33 p. (Studies in Computational Intelligence; vol. 285).

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  • Practical assessment of neural network applications

    Nabney, I. T., Paven, M. J. S., Eldridge, R. C. & Lee, C., 1997, SafeComp 97: Proceedings of the 16th International Conference on Computing Safety, Reliability and Security. Daniel, P. (ed.). London: Springer, p. 357-368 12 p.

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  • Prediction of paroxysmal atrial fibrillation

    Woodcock, D. & Nabney, I. T., 2005, Proceedings of the 2nd International Conference on Computational Intelligence in Medicine and Healthcare (CIMED2005). Plymouth: BIOPATTERN Network of Excellence, p. 376-382 7 p.

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  • Reference scenarios for self-aware computing

    Kephart, J. O., Maggio, M., Diaconescu, A., Giese, H., Hoffmann, H., Kounev, S., Koziolek, A., Lewis, P., Robertsson, A. & Spinner, S., 21 Feb 2017, Self-Aware Computing Systems. Springer, p. 87-106 20 p.

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  • Robust automatic mapping algorithms in a network monitoring scenario

    Ingram, B. R., Cornford, D. & Csató, L., 29 May 2010, geoENV VII – Geostatistics for Environmental Applications: proceedings of the seventh European Conference on Geostatistics for Environmental Applications. Springer, Vol. 16. p. 359-370 12 p.

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  • Rule induction for data exploration

    Nabney, I. T. & Grasl, O., 1991, Proceedings of Avignon 91: Expert systems and their applications. EC2 et Cie, Vol. 1. p. 329-341 13 p.

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  • Second international workshop on models@run.time

    Bencomo, N., France, R. & Blair, G., 2008, Models in software engineering: workshops and symposia at MoDELS 2007, Nashville, TN, USA, September 30 - October 5, 2007, reports and revised selected papers. Giese, H. (ed.). Berlin (DE): Springer, p. 206-211 6 p. (Lecture notes in computer science; no. 5002).

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  • Self-adaptation in Collective Self-aware Computing Systems

    Kephart, J. O., Diaconescu, A., Giese, H., Robertsson, A., Abdelzaher, T., Lewis, P., Filieri, A., Esterle, L. & Frey, S., 21 Feb 2017, Self-Aware Computing Systems. Springer, p. 401-435 35 p.

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  • Self-aware computing systems: related concepts and research areas

    Cámara, J., Bellman, K. L., Kephart, J. O., Autili, M., Bencomo, N., Diaconescu, A., Giese, H., Götz, S., Inverardi, P., Kounev, S. & Tivoli, M., 1 Jan 2017, Self-Aware Computing Systems. Springer, p. 17-49 33 p.

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  • Self-modeling and self-awareness

    Bellman, K. L., Landauer, C., Nelson, P., Bencomo, N., Götz, S., Lewis, P. & Esterle, L., 21 Feb 2017, Self-Aware Computing Systems. Springer, p. 279-304 26 p.

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  • Shape from photographs: a multi-view stereo pipeline

    Hernández, C. & Vogiatzis, G., 2010, Computer vision: detection, recognition and reconstruction. Cipolla, R., Battiato, S. & Farinella, G. M. (eds.). Berlin (US): Springer, p. 281-311 31 p. (Studies in Computational Intelligence; vol. 285).

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  • Software engineering techniques for the development of systems of systems

    Calinescu, R. C. & Kwiatkowska, M. Z., 20 Apr 2010, Foundations of Computer Software: Future Trends and Techniques for Development. Berlin (DE): Springer, p. 59-82 24 p. (Lecture Notes in Computer Science; vol. 6028).

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  • The challenge of real-time automatic mapping for environmental monitoring network management

    Pebesma, E. J., Dubois, G. & Cornford, D., 11 Mar 2008, geoENV VI – Geostatistics for Environmental Applications Proceedings of the Sixth European Conference on Geostatistics for Environmental Applications. Springer, Vol. 15. p. 467-475 9 p.

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  • The notion of self-aware computing

    Kounev, S., Lewis, P., Bellman, K. L., Bencomo, N., Camara, J., Diaconescu, A., Esterle, L., Geihs, K., Giese, H., Götz, S., Inverardi, P., Kephart, J. O. & Zisman, A., 21 Feb 2017, Self-Aware Computing Systems. Springer, p. 3-16 14 p.

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  • Time delay estimation with hidden Markov models

    Azzouzi, M. & Nabney, I. T., 1999, Ninth International Conference on Artificial Neural Networks, 1999 (ICANN). Edinburgh, UK: IEEE, Vol. 1. p. 473-478 6 p.

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  • Towards a framework for the levels and aspects of self-aware computing systems

    Lewis, P., Bellman, K. L., Landauer, C., Esterle, L., Glette, K., Diaconescu, A. & Giese, H., 21 Feb 2017, Self-Aware Computing Systems. Springer, p. 51-85 35 p.

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