Open Access
E3S Web Conf.
Volume 229, 2021
The 3rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)
Article Number 01057
Number of page(s) 7
Published online 25 January 2021
  1. D. Dasgupta, Z. Akhtar, S. Sen, The Journal of Defense Modeling and Simulation 0, 1548512920951275 (0), [Google Scholar]
  2. R. Caruana, Machine Learning 28, 41 (1997) [CrossRef] [Google Scholar]
  3. N. Sadawi, I. Olier, J. Vanschoren, J.N. van Rijn, J. Besnard, R. Bickerton, C. Grosan, L. Soldatova, R.D. King, Journal of Cheminformatics 11, 68 (2019) [CrossRef] [PubMed] [Google Scholar]
  4. S.J. Pan, Q. Yang, IEEE Trans. on Knowl. and Data Eng. 22, 1345 (2010) [CrossRef] [Google Scholar]
  5. J. Zhou, J. Chen, J. Ye, Multi-task learning: Theory, algorithms, and applications, [Google Scholar]
  6. G. Draper-Gil, A.H. Lashkari, M.S.I. Mamun, A.A. Ghorbani, Characterization of Encrypted and VPN Traffic using Time-related Features, in ICISSP (2016) [Google Scholar]
  7. C.I. for Cybersecurity, Intrusion detection evaluation dataset (cic-ids2017), [Google Scholar]
  8. R. Di Pietro, L.V. Mancini, Intrusion Detection Systems, 1st edn. (Springer Publishing Company, Incorporated, 2008), ISBN 0387772650 [Google Scholar]
  9. M.M. Deza, E. Deza, Encyclopedia of Distances (Springer Berlin Heidelberg, 2009) [CrossRef] [Google Scholar]
  10. C. Shui, M. Abbasi, L. Robitaille, B. Wang, C. Gagné, CoRR abs/1903.09109 (2019), 1903.09109 [Google Scholar]
  11. S. Ben-David, R.S. Borbely, Mach. Learn. 73, 273–287 (2008) [CrossRef] [Google Scholar]
  12. J. Baxter, Mach. Learn. 28, 7–39 (1997) [CrossRef] [Google Scholar]
  13. L. Duong, T. Cohn, S. Bird, P. Cook, Low Resource Dependency Parsing: Cross-lingual Parameter Sharing in a Neural Network Parser, in Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers) (Association for Computational Linguistics, Beijing, China, 2015), pp. 845–850, [Google Scholar]
  14. Y. Yang, T.M. Hospedales, CoRR abs/1606.04038 (2016), 1606.04038 [Google Scholar]
  15. S. Vandenhende, S. Georgoulis, W.V. Gansbeke, M. Proesmans, D. Dai, L.V. Gool, Multi-task learning for dense prediction tasks: A survey (2020), 2004.13379 [Google Scholar]
  16. S. Rezaei, X. Liu, Multitask Learning for Network Traffic Classification, in 2020 29th International Conference on Computer Communications and Networks (ICCCN) (2020), pp. 1–9 [Google Scholar]
  17. H. Huang, H. Deng, J. Chen, L. Han, W. Wang, International Journal of Emerging Technologies in Learning (iJET) 13, 4 (2018) [CrossRef] [Google Scholar]
  18. S. Rezaei, X. Liu, A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning, in International Conference on Learning Representations (2020), [Google Scholar]
  19. B. Alothman, International Journal of Intelligent Computing Research (IJICR) 9, 880– (2018) [CrossRef] [Google Scholar]
  20. B. Alothman, H. Janicke, S.Y. Yerima, Class Balanced Similarity-Based Instance Transfer Learning for Botnet Family Classification, in Discovery Science, edited by L. Soldatova, J. Vanschoren, G. Papadopoulos, M. Ceci (Springer International Publishing, Cham, 2018), pp. 99–113, ISBN 978-3-03001771-2 [Google Scholar]
  21. Y. Zhang, Q. Yang, CoRR abs/1707.08114 (2017), 1707.08114 [Google Scholar]
  22. G. Santafe, I.n. Inza, J.A. Lozano, Artif. Intell. Rev. 44, 467 (2015) [CrossRef] [Google Scholar]

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