Browse by Research Project Code

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0

Savva, F. , Anagnostopoulos, C. and Triantafillou, P. (2020) Adaptive learning of aggregate analytics under dynamic workloads. Future Generation Computer Systems, 109, pp. 317-330. (doi: 10.1016/j.future.2020.03.063)

Anagnostopoulos, C. (2020) Edge-centric inferential modeling & analytics. Journal of Network and Computer Applications, 164, 102696. (doi: 10.1016/j.jnca.2020.102696)

Husmeier, D. and Paun, L. M. (2020) Closed-loop effects in coupling cardiac physiological models to clinical interventions. In: Irigoien, I., Lee, D.-J., Martínez-Minaya, J. and Rodríguez-Álvarez, M. X. (eds.) Proceedings of the 35th International Workshop on Statistical Modelling. Servicio Editorial de la Universidad del País Vasco: Bilbao, Spain, pp. 120-125. ISBN 9788413192673

Savva, F. , Anagnostopoulos, C. , Triantafillou, P. and Kolomvatsos, K. (2020) Large-scale data exploration using explanatory regression functions. ACM Transactions on Knowledge Discovery from Data, (Accepted for Publication)

Williamson, J. H. , Quek, M., Popescu, I., Ramsay, A. and Murray-Smith, R. (2020) Efficient human-machine control with asymmetric marginal reliability input devices. PLoS ONE, 15(6), e0233603. (doi: 10.1371/journal.pone.0233603)

Savva, F. , Anagnostopoulos, C. and Triantafillou, P. (2020) SuRF: Identification of Interesting Data Regions with Surrogate Models. In: 36th IEEE International Conference on Data Engineering (IEEE ICDE), Dallas, TX, USA, 20-24 April 2020, pp. 1321-1332. ISBN 9781728129037 (doi:10.1109/ICDE48307.2020.00118)

Anagnostopoulos, C. and Kolomvatsos, K. (2020) Predictive intelligence of reliable analytics in distributed computing environments. Applied Intelligence, (doi: 10.1007/s10489-020-01712-5) (Early Online Publication)

Savva, F. , Anagnostopoulos, C. and Triantafillou, P. (2020) Aggregate Query Prediction under Dynamic Workloads. In: 2019 IEEE International Conference on Big Data (IEEE BigData 2019), Los Angeles, CA, USA, 09-12 Dec 2019, pp. 671-676. ISBN 9781728108582 (doi:10.1109/BigData47090.2019.9006267)

Anagnostopoulos, C. and Triantafillou, P. (2020) Large-scale predictive modeling and analytics through regression queries in data management systems. International Journal of Data Science and Analytics, 9(1), pp. 17-55. (doi: 10.1007/s41060-018-0163-5)

Ireland, D.G. , Doring, M., Glazier, D.I., Haidenbauer, J., Mai, M., Murray-Smith, R. and Ronchen, D. (2019) Kaon photoproduction and the Lambda decay parameter alpha. Physical Review Letters, 123, 182301. (doi: 10.1103/PhysRevLett.123.182301)

Wandy, J., Davies, V., van der Hooft, J. J.J. , Weidt, S., Daly, R. and Rogers, S. (2019) In silico optimization of mass spectrometry fragmentation strategies in metabolomics. Metabolites, 9(10), 219. (doi: 10.3390/metabo9100219) (PMID:31600991)

Jadidinejad, A. , Macdonald, C. and Ounis, I. (2019) How Sensitive is Recommendation Systems' Offline Evaluation to Popularity? In: REVEAL 2019 Workshop at RecSys, Copenhagen, Denmark, 20 Sep 2019,

Davies, V. , Harvey, W. T., Reeve, R. and Husmeier, D. (2019) Improving the identification of antigenic sites in the H1N1 Influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(4), pp. 859-885. (doi: 10.1111/rssc.12338)

Tonolini, F., Jensen, B. S. and Murray-Smith, R. (2019) Variational Sparse Coding. In: Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, 22-25 July 2019,

Savva, F. , Anagnostopoulos, C. and Triantafillou, P. (2019) Explaining Aggregates for Exploratory Analytics. In: IEEE Big Data 2018, Seattle, WA, USA, 10-13 Dec 2018, pp. 478-487. ISBN 9781538650356 (doi:10.1109/BigData.2018.8621953)

Jadidinejad, A. H. , Macdonald, C. and Ounis, I. (2019) Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks. In: 5th ACM SIGIR International Conference on the Theory of Information Retrieval, Santa Clara, CA, USA, 02-05 Oct 2019, pp. 149-151. ISBN 9781450368810 (doi:10.1145/3341981.3344225)

Moran, O., Caramazza, P., Faccio, D. and Murray-Smith, R. (2018) Deep, Complex, Invertible Networks for Inversion of Transmission Effects in Multimode Optical Fibres. In: 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, Canada, 02-08 Dec 2018,

This list was generated on Sun Aug 9 10:20:06 2020 BST.