| Reinforcement learning with imitation for cavity filter tuning S Lindståh, X Lan 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2020 | 9 | 2020 |
| Measurement-based admission control in sliced networks: A best arm identification approach S Lindståhl, A Proutiere, A Johnsson GLOBECOM 2022-2022 IEEE Global Communications Conference, 1484-1490, 2022 | 7 | 2022 |
| Change point detection with adaptive measurement schedules for network performance verification S Lindståhl, A Proutiere, A Johnsson Proceedings of the ACM on Measurement and Analysis of Computing Systems 7 (3 …, 2023 | 2 | 2023 |
| Predictive bandits S Lindståhl, A Proutiere, A Johnsson 2020 59th IEEE Conference on Decision and Control (CDC), 1170-1176, 2020 | 1 | 2020 |
| Change Point Detection with Adaptive Measurement Schedules for Network Performance Verification S Lindståhl, A Proutiere, A Johnsson ACM SIGMETRICS Performance Evaluation Review 52 (1), 83-84, 2024 | | 2024 |
| RoME-QCD: Robust and Measurement Efficient Quickest Change Detection in 5G Networks S Lindståhl, A Proutiere, A Johnsson 2024 8th Network Traffic Measurement and Analysis Conference (TMA), 1-11, 2024 | | 2024 |
| Adaptive Measurement Strategies for Network Optimization and Control S Lindståhl KTH Royal Institute of Technology, 2023 | | 2023 |
| Reinforcement Learning with Imitation for Cavity Filter Tuning: Solving problems by throwing DIRT at them S Lindståhl | | 2019 |
| Optimal konsumtion medstokastisk utsignalstörning M Granberg Olsson, S Lindståhl | | 2017 |
