Paal Engelstad

Vitenskapelige publikasjoner

Holen, Martin; Ruud, Else-Line Malene; Warakagoda, Narada Dilp; Granmo, Ole-Christoffer; Engelstad, Paal E.; Knausgård, Kristian Muri (2022). Towards Using Reinforcement Learning for Autonomous Docking of Unmanned Surface Vehicles. Iliadis, Lazaros; Jayne, Chrisina; Tefas, Anastasios; Pimenidis, Elias (Red.). Engineering Applications of Neural Networks. EANN 2022. Communications in Computer and Information Science. Chapter. s. 461-474. Springer Nature.
http://hdl.handle.net/10852/100544

Meng, Li; Goodwin, Morten; Yazidi, Anis; Engelstad, Paal (2022). Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise. 10 s. IEEE Transactions on Games (TG) .
http://hdl.handle.net/10852/99676

Meng, Li; Yazidi, Anis; Goodwin, Morten; Engelstad, Paal (2022). Expert Q-learning: Deep Reinforcement Learning with Coarse State Values from Offline Expert Examples. 9 s. Proceedings of the Northern Lights Deep Learning Workshop .
https://hdl.handle.net/11250/3046199

Bentsen, Lars Ødegaard; Warakagoda, Narada Dilp; Stenbro, Roy; Engelstad, Paal (2022). Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures. 13 s. Applied Energy . Vol. 333.
https://hdl.handle.net/11250/3042606

Bentsen, Lars Ødegaard; Warakagoda, Narada Dilp; Stenbro, Roy; Engelstad, Paal (2022). Probabilistic Wind Park Power Prediction using Bayesian Deep Learning and Generative Adversarial Networks. 10 s. Journal of Physics: Conference Series (JPCS) . Vol. 2362.
https://hdl.handle.net/11250/3036044

Abolghasemi, Roza; Khadka, Rabindra; Lind, Pedro; Engelstad, Paal E.; Viedma, Enrique Herrera; Yazidi, Anis (2022). Predicting missing pairwise preferences from similarity features in group decision making. Knowledge-Based Systems . Vol. 256.
https://hdl.handle.net/11250/3028362

Rauniyar, Ashish; Østerbø, Olav Norvald; Håkegård, Jan Erik; Engelstad, Paal E. (2022). Secrecy Performance Analysis of Cooperative Nonorthogonal Multiple Access in IoT Networks. IEEE Sensors Journal . Vol. 22.
https://hdl.handle.net/11250/3026184

Bentsen, Lars Ødegaard; Warakagoda, Narada Dilp; Stenbro, Roy; Engelstad, Paal (2022). Wind Park Power Prediction: Attention-Based Graph Networks and Deep Learning to Capture Wake Losses. Journal of Physics: Conference Series (JPCS) . Vol. 2265.
http://hdl.handle.net/10852/98426

Aryan, Ramtin; Yazidi, Anis; Brattensborg, Frode Henriksen; Kure, Øivind; Engelstad, Paal E. (2022). SDN Spotlight: A real-time OpenFlow troubleshooting framework. Future generations computer systems . Vol. 133.
http://hdl.handle.net/10852/93778

Abolghasemi, Roza; Engelstad, Paal E.; Herrera-Viedma, Enrique; Yazidi, Anis (2022). A personality-aware group recommendation system based on pairwise preferences. Information Sciences . Vol. 595.
http://hdl.handle.net/10852/93770

Forskningsrapporter

Østerbø, Olav Norvald; Engelstad, Paal E. (2008). WLAN QoS Analysis - A New Modelling Approach for 802.11e, Telenor R&I Scientific Report, R28/08. 20 s.

Jønvik, Tore; Engelstad, Paal; Do, Thanh van (2005). Towards the realisation of the Virtual Device Consept. 222 s. Unipub forlag.

Engelstad, Paal E. (2000). Scientific Structures and Research Programs in Digital Communication. 20 s.

Formidling

Aryan, Ramtin; Brattensborg, Frode; Yazidi, Anis; Engelstad, Paal E. (2019). Checking the OpenFlow Rule Installation and Operational Verification. The 44th IEEE Conference on Local Computer Networks (LCN). IEEE.

HaileselassieHagos, Desta; Engelstad, Paal E.; Yazidi, Anis (2019). Classification of Delay-based TCP Algorithms From Passive Traffic Measurements. ©2019 IEEE. IEEE.

Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E. (2018). An Incremental Approach for Swift OpenFlow Anomaly Detection. 2018 IEEE 43rd Conference on Local Computer Networks (LCN). IEEE.

Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E.; Kure, Øivind (2017). A General Formalism for Defining and Detecting OpenFlow Rule Anomalies. 2017 IEEE 42nd Conference on Local Computer Networks. IEEE 42nd Conference on Local Computer Networks.

Kongsgård, Kyrre Wahl; Nordbotten, Nils Agne; Mancini, Federico; Engelstad, Paal E. (2017). An Internal/Insider Threat Score for Data Loss Prevention and Detection. Proceedings of the 3rd ACM on International Workshop on Security And Privacy Analytics..

Van Thuan, Do; Engelstad, Paal E.; Feng, Boning; Do, van Thanh (2017). Detection of DNS tunneling in mobile networks using machine learning. International Conference on Information Science and Applications 2017 ICISA 2017.

Do, van Thanh; Engelstad, Paal E.; Feng, Boning; Do, Van Thuan (2017). A near real time SMS Grey Traffic detection. 6th International Conference on Software and Computer Applications.

Kongsgård, Kyrre Wahl; Nordbotten, Nils Agne; Engelstad, Paal E.; Mancini, Federico (2017). Data Loss Prevention for Cross-Domain Instant Messaging. IEEE Symposium Series on Computational Intelligence.

Do, Van Thuan; Engelstad, Paal E.; Boning, Feng; Do, van Thanh (2016). Strengthening mobile network security using machine learning. 13th International Conference on Mobile Web and Intelligent Information Systems. Natalia Kryvinska, University of Vienna, Austria.

Engelstad, Paal E.; Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander (2015). Advanced Classification Lists (Dirty Word Lists) for Automatic Security Classification. International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC).