| Statistical Learning Theory for Control: A Finite-Sample Perspective A Tsiamis, I Ziemann, N Matni, GJ Pappas IEEE Control Systems Magazine 43 (6), 67-97, 2023 | 28 | 2023 |
| Parameter privacy versus control performance: Fisher information regularized control I Ziemann, H Sandberg 2020 American Control Conference (ACC), 1259-1265, 2020 | 14 | 2020 |
| Regret lower bounds for learning linear quadratic gaussian systems I Ziemann, H Sandberg arXiv preprint arXiv:2201.01680, 2022 | 13 | 2022 |
| Single trajectory nonparametric learning of nonlinear dynamics IM Ziemann, H Sandberg, N Matni conference on Learning Theory, 3333-3364, 2022 | 12 | 2022 |
| Learning to control linear systems can be hard A Tsiamis, IM Ziemann, M Morari, N Matni, GJ Pappas Conference on Learning Theory, 3820-3857, 2022 | 10 | 2022 |
| On uninformative optimal policies in adaptive lqr with unknown b-matrix I Ziemann, H Sandberg Learning for Dynamics and Control, 213-226, 2021 | 10 | 2021 |
| Regret Lower Bounds for Unbiased Adaptive Control of Linear Quadratic Regulators I Ziemann, H Sandberg | 10 | 2019 |
| Learning with little mixing I Ziemann, S Tu Advances in Neural Information Processing Systems 35, 4626-4637, 2022 | 9 | 2022 |
| On a phase transition of regret in linear quadratic control: The memoryless case I Ziemann, H Sandberg IEEE Control Systems Letters 5 (2), 695-700, 2020 | 9 | 2020 |
| How are policy gradient methods affected by the limits of control? I Ziemann, A Tsiamis, H Sandberg, N Matni 2022 IEEE 61st Conference on Decision and Control (CDC), 5992-5999, 2022 | 8 | 2022 |
| Noninvasively improving the orbit-response matrix while continuously correcting the orbit I Ziemann, V Ziemann Physical Review Accelerators and Beams 24 (7), 072804, 2021 | 5 | 2021 |
| Model reduction of semistable distributed parameter systems I Ziemann, Y Zhou 2019 18th European Control Conference (ECC), 1944-1950, 2019 | 3 | 2019 |
| A note on the smallest eigenvalue of the empirical covariance of causal Gaussian processes I Ziemann IEEE Transactions on Automatic Control, 2023 | 2 | 2023 |
| The noise level in linear regression with dependent data I Ziemann, S Tu, GJ Pappas, N Matni arXiv preprint arXiv:2305.11165, 2023 | 2 | 2023 |
| Resource Constrained Sensor Attacks by Minimizing Fisher Information I Ziemann, H Sandberg 2021 American Control Conference (ACC), 4580-4585, 2021 | 2 | 2021 |
| Applications of information inequalities to linear systems: Adaptive control and security I Ziemann KTH Royal Institute of Technology, 2021 | 2 | 2021 |
| The Fundamental Limitations of Learning Linear-Quadratic Regulators BD Lee, I Ziemann, A Tsiamis, H Sandberg, N Matni arXiv preprint arXiv:2303.15637, 2023 | 1 | 2023 |
| A Tutorial on the Non-Asymptotic Theory of System Identification I Ziemann, A Tsiamis, B Lee, Y Jedra, N Matni, GJ Pappas arXiv preprint arXiv:2309.03873, 2023 | | 2023 |
| Statistical Learning, Dynamics and Control: Fast Rates and Fundamental Limits for Square Loss I Ziemann KTH Royal Institute of Technology, 2022 | | 2022 |
Henrik SandbergProfessor of Decision and Control Systems, KTH Royal Institute of TechnologyVerified email at kth.se
