Results


PUBLICATIONS


Daniela Pohl, Abdelhamid Bouchachia, and Hermann Hellwagner, 2019. Active Online Learning for Social Media: Analysis to Support Crisis Management. To appear in the IEEE Transactions on Knowledge and Data Engineering (TKDE). IEEE Press.

Saad Mohamad, Abdelhamid Bouchachia and Moamar Sayed-Mouchaweh, 2019. Asynchronous Stochastic Variational Inference. To appear in proceedings of the 2019 INNS Big Data and Deep Learning Conference. Lecture Notes in Artificial Intelligence (LNAI), Springer.

W. Jamil, A. Bouchachia, 2019. Competitive Online Regularised Regression. Accepted to appear in the Machine Learning journal, Springer.

W. Jamil, A. Bouchachia, 2018. Model Selection in Online Learning for Times Series Forecasting. The 18th UK Workshop on Computational Intelligence. Springer.

W. Jamil, N.-C. Duong, W. Wang, C. Mansouri, S. Mohamad, A. Bouchachia, 2018. Scalable online learning for Flink: SOLMA library. The 12th European Conference on Software Architecture. ACM.  DOI:  https://dl.acm. org/citation.cf m?id=3241438

S. Mohamad, M.S. Mouchaweh, A. Bouchachia, 2018. Active learning for classifying data streams with unknown number of classes. Elsevier Neural Networks vol 98. DOI: https://www.s ciencedirect.com/science/article/pii/S0893608017302435.

D. Pohl, A. Bouchachia, H. Hellwagner, 2018. Batch-based active learning: Application to social media data for crisis management. Elsevier Expert Syst. Appl vol 93. DOI: https://doi.org/10.1016/j.eswa.2017.10.026

A. Lotfi, A. Bouchachia, A. Gegov, C. Langensiepen, T. McGinnity. Advances in Computational Intelligence Systems, 2018 .The 18th UK Workshop on Computational Intelligence. Springer. DOI: https://link.spr inger.com/boo kseries/11156

Jeyhun Karimov ; Tilmann Rabl ; Asterios Katsifodimos ; Roman Samarev ; Henri Heiskanen ; Volker Markl, 2018. Benchmarking Distributed Stream Data Processing Engines. IEEE 34th International Conference on Data Engineering (ICDE). IEEE. DOI: https://ieeexpl ore.ieee.org/document/8509 390.

A. Kunft, AsteriosKatsifodimos, Sebastian Schelter, Tilmann. Blockjoin, 2018: efficient matrix partitioning through joins. Proceedings of the VLDB Endowment. ACM Volume 10, Issue 13.

J. Traub,P. Grulich, A. R. Cuellar, S. Breß, A. Katsifodimos, T. Rabl,V. Markl. IEEE International Conference on Data Engineering (ICDE). IEEE. DOI:Scotty: EfficientWindow Aggregationfor out-of- orderStreamProcessing

M.S. Mouchaweh, A. Bifet, A. Bouchachia, J. Gama, R. Ribeiro. 2017. ECML/PKDD 2017 Workshop on IoT Large Scale Learning from Data Streams. CEUR. DOI: http://dblp.org
/db/conf/pkdd/iotstreaming2017.html

J. J. Rubio, A. Bouchachia. 2017. MSAFIS: an evolving fuzzy inference system. Softcomputing. Springer Vol. 21, No. 9. DOI: http://link.springer.com/article/10.1007/s00500-015-1946-4

A. Bouchachia. 2016. Fuzzy Classifiers. Handbook on Computational Intelligence. World Scientific. DOI: http://www.worldscientific. com/worldscibooks/10.1142/9548

Andreas Kunft, Alexander Alexandrov, Asterios Katsifodimos, and Volker Markl. 2016. Bridging the gap: towards optimization across linear and relational algebra. In Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR '16). ACM, New York, NY, USA, , Article 1 , 4 pages. DOI: http://dx.doi.org/10.1145/2926534.2926540

Alexander Alexandrov, Andreas Salzmann, Georgi Krastev, Asterios Katsifodimos, and Volker Markl. 2016. Emma in Action: Declarative Dataflows for Scalable Data Analysis. In Proceedings of the 2016 International Conference on Management of Data (SIGMOD '16). ACM, New York, NY, USA, 2073-2076. DOI: https://doi.org/10.1145/2882903.2899396

Alexander Alexandrov, Asterios Katsifodimos, Georgi Krastev, and Volker Markl. 2016. Implicit Parallelism through Deep Language Embedding. SIGMOD Rec. 45, 1 (June 2016), 51-58. DOI: http://dx.doi.org/10.1145/2949741.2949754

Ignacio García, Rubén Casado and Abdelhamid Bouchachia, "An Incremental Approach for Real-Time Big Data Visual Analytics," IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), Vienna, 2016, pp. 177-182. DOI: https://doi.org/10.1109/W-FiCloud.2016.46

Roberto Díaz Morales and Ángel Navia Vázquez, 2016. "Improving the efficiency of IRWLS SVMs using parallel Cholesky factorization", Pattern Recognition Letters, Volume 84, 1 December 2016, Pages 91-98, ISSN 0167-8655. DOI: http://dx.doi.org/10.1016/j.patrec.2016.08.015

S. Mohamad; A. Bouchachia; M. Sayed-Mouchaweh, "A Bi-Criteria Active Learning Algorithm for Dynamic Data Streams," in IEEE Transactions on Neural Networks and Learning Systems , vol.PP, no.99, pp.1-13. DOI: https://doi.org/10.1109/TNNLS.2016.2614393 

Jamil, W., Kalnishkan, Y. and Bouchachia, A., 2016. "Aggregation Algorithm Vs. Average for Time Series Prediction". In: ECML/PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV-2016), 19-23 September 2016, Riva del Garda, Italy. Open Access at: http://eprints.bournemouth.ac.uk/24798/

Saad Mohamad, Moamar Sayed-Mouchaweh and Abdelhamid Bouchachia, 2016. "Active Learning for Data Streams under Concept Drift and concept evolution". In: ECML/PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV-2016), 19-23 September 2016, Riva del Garda, Italy. 

P. Carbone, S.Ewen, S.haridi, A. Katsifodimos, V. Markl, K. Tzoumas 2015. Apache Flink: Stream and Batch Processing in a Single Engine. Vol. 38 No. 4, Issue on Next- Generation Stream Processing Systems.DOI: http://sites.computer.org/de bull/A15dec/p 28.pdf

S. Mohamad, A. Bouchachia and M. Sayed-Mouchaweh, "A non-parametric hierarchical clustering model," 2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), Douai, 2015, pp. 1-7. DOI: https://doi.org/10.1109/EAIS.2015.7368803