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Alina Sirbu
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A. Sirbu
,
Loreto, V.
,
Servedio, V. D. P.
, and
Tria, F.
,
“
Opinion dynamics with disagreement and modulated information
”
,
Journal of Statistical Physics
, pp. 1–20, 2013.
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A. Sirbu
,
Becker, M.
,
Caminiti, S.
,
De Baets, B.
,
Elen, B.
,
Francis, L.
,
Gravino, P.
,
Hotho, A.
,
Ingarra, S.
,
Loreto, V.
,
Molino, A.
,
Mueller, J.
,
Peters, J.
,
Ricchiuti, F.
,
Saracino, F.
,
Servedio, V. D. P.
,
Stumme, G.
,
Theunis, J.
,
Tria, F.
, and
Van den Bossche, J.
,
“
Participatory Patterns in an International Air Quality Monitoring Initiative.
”
,
PLoS One
, vol. 10, p. e0136763, 2015.
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A. Sirbu
,
Kerr, G.
,
Crane, M.
, and
Ruskin, H. J.
,
“
RNA-Seq vs dual- and single-channel microarray data: sensitivity analysis for differential expression and clustering.
”
,
PLoS One
, vol. 7, p. e50986, 2012.
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A. Sirbu
,
Ruskin, H. J.
, and
Crane, M.
,
“
Integrating heterogeneous gene expression data for gene regulatory network modelling.
”
,
Theory Biosci
, vol. 131, pp. 95-102, 2012.
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A. Sirbu
,
Ruskin, H. J.
, and
Crane, M.
,
“
Cross-platform microarray data normalisation for regulatory network inference.
”
,
PLoS One
, vol. 5, p. e13822, 2010.
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A. Sirbu
,
Ruskin, H. J.
, and
Crane, M.
,
“
Comparison of evolutionary algorithms in gene regulatory network model inference.
”
,
BMC Bioinformatics
, vol. 11, p. 59, 2010.
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A. Sirbu
and
Babaoglu, O.
,
“
A Holistic Approach to Log Data Analysis in High-Performance Computing Systems: The Case of IBM Blue Gene/Q
”
, in
Euro-Par 2015: parallel Processing Workshops, LNCS 9523
, 2015.
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A. Sirbu
and
Babaoglu, O.
,
“
Towards Data-Driven Autonomics in Data Centers
”
, in
IEEE International Conference on Cloud and Autonomic Computing
, 2015.
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A. Sirbu
,
Crane, M.
, and
Ruskin, H. J.
,
“
Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks
”
,
Microarrays
, vol. 4, pp. 255–269, 2015.
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A. Sirbu
and
Babaoglu, O.
,
“
Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer
”
,
22nd International European Conference on Parallel and Distributed Computing, Euro-Par 2016
, vol. LNCS 9833. Springer LNCS, Grenoble, France, 2016.
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A. Sirbu
,
Crane, M.
, and
Ruskin, H. J.
,
“
EGIA–Evolutionary Optimisation of Gene Regulatory Networks, an Integrative Approach
”
, in
Complex Networks V
, Springer International Publishing, 2014, pp. 217–229.
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A. Sirbu
,
Loreto, V.
,
Servedio, V. D. P.
, and
Tria, F.
,
“
Cohesion, consensus and extreme information in opinion dynamics
”
,
Advances in Complex Systems
, vol. 16, p. 1350035, 2013.
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A. Sirbu
,
Ruskin, H. J.
, and
Crane, M.
,
“
Stages of Gene Regulatory Network Inference: the Evolutionary Algorithm Role
”
, in
Evolutionary Algorithms
, InTech, 2011.
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A. Sirbu
,
Ruskin, H. J.
, and
Crane, M.
,
“
Regulatory network modelling: Correlation for structure and parameter optimisation
”
,
Proceedings of The IASTED Technology Conferences (International Conference on Computational Bioscience), Cambridge, Massachusetts
, pp. 3473–3481, 2010.
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A. Sirbu
and
Babaoglu, O.
,
“
Towards operator-less data centers through data-driven, predictive, proactive autonomics
”
,
Cluster Computing
, pp. 1–14, 2016.
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A. Sirbu
,
Loreto, V.
,
Servedio, V. D. P.
, and
Tria, F.
,
“
Opinion dynamics: models, extensions and external effects
”
, in
Participatory Sensing, Opinions and Collective Awareness
, Springer, 2017, pp. 363–401.
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A. Sirbu
and
Babaoglu, O.
,
“
Predicting System-level Power for a Hybrid Supercomputer
”
, in
2016 International Conference on High Performance Computing Simulation (HPCS)
, Innsbruck, Austria, 2016.
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A. Sirbu
,
Pedreschi, D.
,
Giannotti, F.
, and
Kertész, J.
,
“
Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model
”
,
PloS one
, vol. 14, p. e0213246, 2019.
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A. Sirbu
,
Giannotti, F.
,
Pedreschi, D.
, and
Kertész, J.
,
“
Public opinion and Algorithmic bias
”
,
ERCIM News
, 2019.
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A. Sirbu
,
Andrienko, G.
,
Andrienko, N.
,
Boldrini, C.
,
Conti, M.
,
Giannotti, F.
,
Guidotti, R.
,
Bertoli, S.
,
Kim, J.
,
Muntean, C. Ioana
,
Pappalardo, L.
,
Passarella, A.
,
Pedreschi, D.
,
Pollacci, L.
,
Pratesi, F.
, and
Sharma, R.
,
“
Human migration: the big data perspective
”
,
International Journal of Data Science and Analytics
, pp. 1–20, 2020.
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