Daniela Pohl, Abdelhamid Bouchachia, and Hermann Hellwagner, 2019. Active Online Learning for Social Media: Analysis to Support Crisis Management. IEEE Transactions on Knowledge and Data Engineering (TKDE), In press. DOI: 10.1109/TKDE.2019.2906173.
Saad Mohamad, Abdelhamid Bouchachia and Moamar Sayed-Mouchaweh, 2019. Asynchronous Stochastic Variational Inference. Proceedings of the 2019 INNS Big Data and Deep Learning Conference, LNAI, Springer, DOI: https://link.springer.com/chapter/10.1007/978-3-030-16841-4_31.
Waqas Jamil, Abdelhamid Bouchachia, 2019. Online Bayesian Shrinkage Regression. Proceedings of the 27 th European Symposium on Artificial Neural Networks. Bruges, 24-26 April 2019.
Bartnik, A., Del Monte, B., Rabl, T, & Markl, V., 2019. On-the-fly Reconfiguration of Query Plans for Stateful Stream Processing Engines. In BTW 2018. [This research was conducted as part of the PROTEUS and STREAMLINE projects].
W. Jamil, A. Bouchachia, 2018. Model Selection in Online Learning for Times Series Forecasting. The 18th UK Workshop on Computational Intelligence. pp: 83-95, https://link.springer.com/chapter/10.1007/978-3-319-97982-3_7 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:10.1145/3241403.3241438.
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://doi.org/10.1016/j.neunet.2017.10.004
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.springer.com/book/10.1007/978-3-319-97982-3
Karimov, J., Rabl, T., & Markl, V. (2018, August). PolyBench: The First Benchmark for Polystores. In Technology Conference on Performance Evaluation and Benchmarking (pp. 24-41). Springer, Cham. [This research was conducted as part of the PROTEUS and STREAMLINE projects]
Jeyhun Karimov ; Tilmann Rabl ; Asterios Katsifodimos ; Roman Samarev ; Henri Heiskanen ; Volker Markl, 2018. Benchmarking Distributed Stream Data Processing Systems. IEEE 34th International Conference on Data Engineering (ICDE). IEEE. DOI: 10.1109/ICDE.2018.00169 [This research was conducted as part of the PROTEUS and STREAMLINE projects]
A. Kunft, AsteriosKatsifodimos, Sebastian Schelter, Tilmann, 2018. Blockjoin: efficient matrix partitioning through joins. Proceedings of the VLDB Endowment. ACM Volume 10, Issue 13. DOI: 10.14778/3151106.3151110 [This research was conducted as part of the PROTEUS and STREAMLINE projects]
J. Traub,P. Grulich, A. R. Cuellar, S. Breß, A. Katsifodimos, T. Rabl,V. Markl. Scotty: Efficient Window Aggregation for out-of- order Stream Processing. IEEE International Conference on Data Engineering (ICDE). IEEE. DOI:10.1109/ICDE.2018.00135
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. http://ceur-ws.org/Vol-1958/
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:https://doi.org/10.1142/9789814675017_0005.
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. DOI: http://dx.doi.org/10.1145/2926534.2926540
Carbone, P., Traub, J., Katsifodimos, A., Haridi, S., & Markl, V. (2016, October). Cutty: Aggregate sharing for user-defined windows. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (pp. 1201-1210). ACM. DOI:10.1145/2983323.2983807. [This research was conducted as part of the PROTEUS and STREAMLINE projects]
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. [This research was conducted as part of the PROTEUS and STREAMLINE projects]
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:10.1145/2949741.2949754. [This research was conducted as part of the PROTEUS and STREAMLINE projects]
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