Back
  1. Home
  2. Profile of Georgios VARISTEAS (Unilu)
Profil

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
1315 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

20 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. Proceedings of 2019 IEEE Vehicular Networking Conference.
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

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

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

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

Contact ORBilu