关注
Ingvar Ziemann
Ingvar Ziemann
在 seas.upenn.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
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
532023
Learning with little mixing
I Ziemann, S Tu
Advances in Neural Information Processing Systems 35, 4626-4637, 2022
252022
Single trajectory nonparametric learning of nonlinear dynamics
IM Ziemann, H Sandberg, N Matni
conference on Learning Theory, 3333-3364, 2022
232022
Regret lower bounds for learning linear quadratic gaussian systems
I Ziemann, H Sandberg
arXiv preprint arXiv:2201.01680, 2022
192022
Parameter privacy versus control performance: Fisher information regularized control
I Ziemann, H Sandberg
2020 American Control Conference (ACC), 1259-1265, 2020
152020
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
142022
A tutorial on the non-asymptotic theory of system identification
I Ziemann, A Tsiamis, B Lee, Y Jedra, N Matni, GJ Pappas
2023 62nd IEEE Conference on Decision and Control (CDC), 8921-8939, 2023
132023
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
132022
On uninformative optimal policies in adaptive lqr with unknown b-matrix
I Ziemann, H Sandberg
Learning for Dynamics and Control, 213-226, 2021
102021
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
82020
Regret Lower Bounds for Unbiased Adaptive Control of Linear Quadratic Regulators
I Ziemann, H Sandberg
82019
The fundamental limitations of learning linear-quadratic regulators
BD Lee, I Ziemann, A Tsiamis, H Sandberg, N Matni
2023 62nd IEEE Conference on Decision and Control (CDC), 4053-4060, 2023
62023
Noninvasively improving the orbit-response matrix while continuously correcting the orbit
I Ziemann, V Ziemann
Physical Review Accelerators and Beams 24 (7), 072804, 2021
52021
Model reduction of semistable distributed parameter systems
I Ziemann, Y Zhou
2019 18th European Control Conference (ECC), 1944-1950, 2019
42019
The noise level in linear regression with dependent data
I Ziemann, S Tu, GJ Pappas, N Matni
Advances in Neural Information Processing Systems 36, 2024
32024
Sharp rates in dependent learning theory: Avoiding sample size deflation for the square loss
I Ziemann, S Tu, GJ Pappas, N Matni
arXiv preprint arXiv:2402.05928, 2024
32024
A note on the smallest eigenvalue of the empirical covariance of causal gaussian processes
I Ziemann
IEEE Transactions on Automatic Control, 2023
32023
Resource Constrained Sensor Attacks by Minimizing Fisher Information
I Ziemann, H Sandberg
2021 American Control Conference (ACC), 4580-4585, 2021
22021
Statistical Learning, Dynamics and Control: Fast Rates and Fundamental Limits for Square Loss
I Ziemann
KTH Royal Institute of Technology, 2022
12022
Applications of information inequalities to linear systems: Adaptive control and security
I Ziemann
KTH Royal Institute of Technology, 2021
12021
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