Rebekka Olsson Omslandseter
PhD Research Fellow
Dr. Rebekka Olsson Omslandseter is passionate about technology, especially the field of artificial intelligence. She has been affiliated with UiA since 2014 and has completed her bachelor's degree, master's degree, and doctoral degree at this university. Rebekka has researched machine learning algorithms that learn through trial, error, and feedback (a process known as reinforcement learning). She has worked on algorithms that can find groupings in data and monitor the compositions of these groups over time (even when the elements to be grouped behave very randomly). Rebekka has explored the use of these algorithms for grouping users in mobile communication networks and has also researched and proposed methods for learning devices to learn even faster and better.
Rebekka completed her bachelor's degree in electronics in 2017, and she completed her master's degree in information and communication technology (ICT) in 2020. In 2019, she began her doctoral work in artificial intelligence (AI) at the Department of ICT at the same university. As an integrated doctoral student, she worked on her master's and doctoral degrees simultaneously for a period. In December 2023, she completed her doctoral degree.
Courses and teaching
Rebekka has taught the following subjects at UiA:
- ELE302 Access in Wireless Networks (formerly ELE215)
- ELE213 Signal Processing
- IKT436 Advanced Internet Services and Protocols
- IKT112 Concepts of Machine Learning
- IKT115 Introduction to Artificial Intelligence Technology
Scientific publications
- Oommen, John; Omslandseter, Rebekka Olsson; Lei, Jiao (2023). Learning automata-based partitioning algorithms for stochastic grouping problems with non-equal partition sizes. Pattern Analysis and Applications. ISSN: 1433-7541. 26s 751 - 772. doi:10.1007/s10044-023-01131-5.
- Omslandseter, Rebekka Olsson; Lei, Jiao; Oommen, John (2023). Pioneering approaches for enhancing the speed of hierarchical LA by ordering the actions. Information Sciences. ISSN: 0020-0255. 647s 1 - 17. doi:10.1016/j.ins.2023.119487.
- Oommen, John; Omslandseter, Rebekka Olsson; Lei, Jiao (2023). The object migration automata: its field, scope, applications, and future research challenges. Pattern Analysis and Applications. ISSN: 1433-7541. 26s 917 - 928. doi:10.1007/s10044-023-01163-x.
- Omslandseter, Rebekka Olsson; Jiao, Lei; Oommen, John (2022). Enhancing the Speed of Hierarchical Learning Automata by Ordering the Actions - A Pioneering Approach. Lecture Notes in Computer Science (LNCS). ISSN: 0302-9743. 13728s 775 - 788. doi:10.1007/978-3-031-22695-3_54.
- Omslandseter, Rebekka Olsson; Jiao, Lei; Zhang, Xuan; Yazidi, Anis; Oommen, John (2022). The Hierarchical Discrete Learning Automaton Suitable for Environments with Many Actions and High Accuracy Requirements. Lecture Notes in Computer Science (LNCS). ISSN: 0302-9743. 13151s 507 - 518. doi:10.1007/978-3-030-97546-3_41.
- Omslandseter, Rebekka Olsson; Jiao, Lei; Zhang, Xuan; Yazidi, Anis; Oommen, John (2022). The Hierarchical Discrete Pursuit Learning Automaton: A Novel Scheme With Fast Convergence and Epsilon-Optimality. IEEE Transactions on Neural Networks and Learning Systems. ISSN: 2162-237X. s 1 - 15. doi:10.1109/TNNLS.2022.3226538.
- Omslandseter, Rebekka Olsson; Lei, Jiao; Liu, Yuanwei; Oommen, John (2022). User grouping and power allocation in NOMA systems: a novel semi-supervised reinforcement learning-based solution. Pattern Analysis and Applications. ISSN: 1433-7541. doi:10.1007/s10044-022-01091-2.
- Omslandseter, Rebekka Olsson; Jiao, Lei; Oommen, John (2021). A Learning-Automata Based Solution for Non-equal Partitioning: Partitions with Common GCD Sizes. Lecture Notes in Computer Science (LNCS). ISSN: 0302-9743. 12799s 227 - 239. doi:10.1007/978-3-030-79463-7_19.
- Omslandseter, Rebekka Olsson; Jiao, Lei; Oommen, John (2021). Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes. IFIP Advances in Information and Communication Technology. ISSN: 1868-4238. doi:10.1007/978-3-030-79150-6_11.
- Omslandseter, Rebekka Olsson; Lei, Jiao; Liu, Yuanwei; Oommen, John (2020). User Grouping and Power Allocation in NOMA Systems: A Reinforcement Learning-Based Solution. Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices.. ISBN: 978-3-030-55789-8. Springer Nature. Artikkel. s 299 - 311.
- Omslandseter, Rebekka Olsson; Lei, Jiao; Haglund, Magne Arild (2019). Field Measurements and Parameter Calibrations of Propagation Model for Digital Audio Broadcasting in Norway. IEEE Vehicular Technology Conference (VTC). ISSN: 1090-3038. doi:10.1109/VTCFall.2018.8690746.
Last changed: 3.02.2024 22:02