DI (FH) Michael Roßbory
M. Kumar, M. Roßbory, B. Moser, B. Freudenthaler. An optimal (∊,δ)-differentially private learning of distributed deep fuzzy model. Information Services, volume online first, DOI: 10.1016/j.ins.2020.07.044, August, 2020.
M. Kumar, M. Roßbory, B. Moser, B. Freudenthaler. Differentially private learning of distributed deep models. MAP '20 Adjunct: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization, pages 193-200, DOI 10.1145/3386392.3399562, ACM, July, 2020.
V. Janjic, J. Bowles, A. Vermeulen, A. Silvina, M. Belk, C. Fidas, A. Pitsillides, M. Kumar, M. Rossbory, M. Vinov, T. Given-Wilson, A. Legay, E. Blackledge, R. Arredouani, G. Stylianou, W. Huang. The SERUMS tool-chain: Ensuring security and privacy of medical data in smart patient-centric healthcare systems. Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData 2019), pages 2726-2735, DOI 10.1109/BigData47090.2019.9005600, IEEE, February, 2020.
M. Kumar, M. Roßbory, B. Moser, B. Freudenthaler. Deriving an optimal noise adding mechanism for privacy-preserving machine learning. In G. Anderst-Kotsis, A. Tjoa, I. Khalil, E. al. (editors), Database and Expert Systems Applications - Proc DEXA 209 International Workshops, Communications in Computer and Information Science, volume 1062, pages 108-118, DOI 10.1007/978-3-030-27684-3_15, Springer, August, 2019.
G. Chasparis, M. Roßbory, V. Janjic, K. Hammond. Learning-based dynamic pinning of parallelized applications in many-core systems. Proceedings of the 27th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP 2019), pages 1-8, DOI 10.1109/EMPDP.2019.8671569, IEEE, February, 2019.
G. Chasparis, M. Rossbory. Efficient dynamic pinning of parallelized applications by distributed reinforcement learning. International Journal of Parallel Programming, Special Issue on High-Level Programming for Heterogeneous Parallel Systems, volume 47, number 1, pages 24-38, DOI: 10.1007/s10766-017-0541-y, November, 2017.
G. Chasparis, M. Roßbory, V. Janjic. Efficient dynamic pinning of parallelized applications by reinforcement learning with applications. In F. Rivera, T. Pena, J. Cabaleiro (editors), uro-Par 2017: Parallel Processing - Proc. Euro-Par 2017, Lecture Notes in Computer Science, volume 10417, pages 164-176, Springer, August, 2017.
M. Moniruzzaman, K. Idrees, M. Roßbory, J. Gracia. An adaptive load-balancer for task-scheduling in FastFlow. Proceedings of the 5th International Conference on Advanced Communications and Computation (INFOCOMP 2015), pages 6-12, IARIA, June, 2015.
M. Roßbory, W. Reisner. Parallelization of algorithms for linear discrete optimization using ParaPhrase. In F. Morvan, A. M. Toja, R. R. Wagner (editors), 24th International Workshop on Database and Expert Systems Applications, pages 241-245, CPS, August, 2013.