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VARISTEAS Georgios

Main Referenced Co-authors
STATE, Radu  (6)
FRANK, Raphaël  (4)
DU, Manxing  (2)
AVANESOV, Tigran  (1)
BRORSSON, Mats  (1)
Main Referenced Keywords
Anomaly Detection (1); Automated Driving (1); Convolutional Neural Networks (1); Credential Authentication Attack (1); end-to-end steering (1);
Main Referenced Disciplines
Computer science (9)

Publications (total 9)

The most downloaded
1396 downloads
DU, M., SASSIOUI, R., VARISTEAS, G., STATE, R., Brorsson, M., & Cherkaoui, O. (2017). Improving Real-Time Bidding Using a Constrained Markov Decision Process. In Proceedings of the 13th International Conference on Advanced Data Mining and Applications (pp. 711-726). Springer. doi:10.1007/978-3-319-69179-4_50 https://hdl.handle.net/10993/33478

The most cited

22 citations (Scopus®)

KAIAFAS, G., VARISTEAS, G., LAGRAA, S., & STATE, R. (2018). Detecting Malicious Authentication Events Trustfully. In G. KAIAFAS, G. VARISTEAS, S. LAGRAA, ... R. STATE, IEEE/IFIP Network Operations and Management Symposium, 23-27 April 2018, Taipei, Taiwan Cognitive Management in a Cyber World. https://hdl.handle.net/10993/35702

ROBINET, F., Demeules, A., FRANK, R., VARISTEAS, G., & HUNDT, C. (2020). Leveraging Privileged Information to Limit Distraction in End-to-End Lane Following. 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC). doi:10.1109/CCNC46108.2020.9045110
Peer reviewed

DU, M., HAMMERSCHMIDT, C., VARISTEAS, G., STATE, R., BRORSSON, M. H., & Zhang, Z. (2019). Time Series Modeling of Market Price in Real-Time Bidding. In 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
Peer reviewed

VARISTEAS, G., FRANK, R., SAJADI ALAMDARI, S. A., VOOS, H., & STATE, R. (2019). Evaluation of End-To-End Learning for Autonomous Driving: The Good, the Bad and the Ugly. In 2nd International Conference on Intelligent Autonomous Systems, Singapore, Feb. 28 to Mar. 2, 2019. IEEE.
Peer reviewed

VARISTEAS, G., & FRANK, R. (2019). JUNIOR, A Research Platform for Connected and Automated Driving. In 2019 IEEE Vehicular Networking Conference (VNC). IEEE. doi:10.1109/VNC48660.2019.9062824
Peer reviewed

Mund, S., FRANK, R., VARISTEAS, G., & STATE, R. (2018). Visualizing the Learning Progress of Self-Driving Cars. In 21st International Conference on Intelligent Transportation Systems (pp. 2358-2363). IEEE.
Peer reviewed

VARISTEAS, G., AVANESOV, T., & STATE, R. (2018). Distributed C++-Python embedding for fast predictions and fast prototyping. In Proceedings of the Second Workshop on Distributed Infrastructures for Deep Learning.
Peer reviewed

KAIAFAS, G., VARISTEAS, G., LAGRAA, S., & STATE, R. (2018). Detecting Malicious Authentication Events Trustfully. In G. KAIAFAS, G. VARISTEAS, S. LAGRAA, ... R. STATE, IEEE/IFIP Network Operations and Management Symposium, 23-27 April 2018, Taipei, Taiwan Cognitive Management in a Cyber World.
Peer reviewed

DU, M., SASSIOUI, R., VARISTEAS, G., STATE, R., Brorsson, M., & Cherkaoui, O. (2017). Improving Real-Time Bidding Using a Constrained Markov Decision Process. In Proceedings of the 13th International Conference on Advanced Data Mining and Applications (pp. 711-726). Springer. doi:10.1007/978-3-319-69179-4_50
Peer reviewed

Goodman, D., VARISTEAS, G., & Harris, T. (2017). Pandia: comprehensive contention-sensitive thread placement. In Proceedings of the Twelfth European Conference on Computer Systems (pp. 254-269). New York, United States: ACM.
Peer reviewed

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