Ingvar M. Ziemann

48 papers A* 7C 2Journal 27Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	A Short Information-Theoretic Analysis of Linear Auto-Regressive Learning. L4DC Ingvar M. Ziemann
2025	J	`jnl`	A Vector Bernstein Inequality for Self-Normalized Martingales. Trans. Mach. Learn. Res. Ingvar M. Ziemann
2025	J	`jnl`	Finite Sample Analysis of Subspace Identification Methods. CoRR Jiabao He, Ingvar M. Ziemann, Cristian R. Rojas, S. Joe Qin, Håkan Hjalmarsson
2025	—	`conf`	Logarithmic Regret for Nonlinear Control. L4DC James Wang, Bruce D. Lee, Ingvar M. Ziemann, Nikolai Matni
2025	J	`jnl`	Logarithmic Regret for Nonlinear Control. CoRR James Wang, Bruce D. Lee, Ingvar M. Ziemann, Nikolai Matni
2025	J	`jnl`	Nearly Instance-Optimal Parameter Recovery from Many Trajectories via Hellinger Localization. CoRR Eliot Shekhtman, Yichen Zhou, Ingvar M. Ziemann, Nikolai Matni, Stephen Tu
2025	—	`conf`	Nonconvex Linear System Identification with Minimal State Representation. L4DC Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, Ingvar M. Ziemann, René Vidal
2025	J	`jnl`	Nonconvex Linear System Identification with Minimal State Representation. CoRR Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, Ingvar M. Ziemann, René Vidal
2025	J	`jnl`	Regret Lower Bounds for Learning Linear Quadratic Gaussian Systems. IEEE Trans. Autom. Control. Ingvar M. Ziemann, Henrik Sandberg
2025	A*	`conf`	Shallow diffusion networks provably learn hidden low-dimensional structure. ICLR Nicholas Matthew Boffi, Arthur Jacot, Stephen Tu, Ingvar M. Ziemann
2025	—	`conf`	State space models, emergence, and ergodicity: How many parameters are needed for stable predictions? L4DC Ingvar M. Ziemann, Nikolai Matni, George J. Pappas
2024	J	`jnl`	A Short Information-Theoretic Analysis of Linear Auto-Regressive Learning. CoRR Ingvar M. Ziemann
2024	—	`conf`	Active Learning for Control-Oriented Identification of Nonlinear Systems. CDC Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni
2024	J	`jnl`	Active Learning for Control-Oriented Identification of Nonlinear Systems. CoRR Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni
2024	—	`conf`	Finite Sample Analysis for a Class of Subspace Identification Methods. CDC Jiabao He, Ingvar M. Ziemann, Cristian R. Rojas, Håkan Hjalmarsson
2024	J	`jnl`	Finite Sample Analysis for a Class of Subspace Identification Methods. CoRR Jiabao He, Ingvar M. Ziemann, Cristian R. Rojas, Håkan Hjalmarsson
2024	A*	`conf`	Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples. ICML Thomas T. C. K. Zhang, Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni
2024	J	`jnl`	Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples. CoRR Thomas T. Zhang, Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni
2024	—	`conf`	Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method. CDC Charis J. Stamouli, Ingvar M. Ziemann, George J. Pappas
2024	J	`jnl`	Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method. CoRR Charis J. Stamouli, Ingvar M. Ziemann, George J. Pappas
2024	J	`jnl`	Shallow diffusion networks provably learn hidden low-dimensional structure. CoRR Nicholas M. Boffi, Arthur Jacot, Stephen Tu, Ingvar M. Ziemann
2024	A*	`conf`	Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss. ICML Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni
2024	J	`jnl`	Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss. CoRR Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni
2024	J	`jnl`	State space models, emergence, and ergodicity: How many parameters are needed for stable predictions? CoRR Ingvar M. Ziemann, Nikolai Matni, George J. Pappas
2023	—	`conf`	A Tutorial on the Non-Asymptotic Theory of System Identification. CDC Ingvar M. Ziemann, Anastasios Tsiamis, Bruce D. Lee, Yassir Jedra, Nikolai Matni, George J. Pappas
2023	J	`jnl`	A Tutorial on the Non-Asymptotic Theory of System Identification. CoRR Ingvar M. Ziemann, Anastasios Tsiamis, Bruce D. Lee, Yassir Jedra, Nikolai Matni, George J. Pappas
2023	—	`conf`	The Fundamental Limitations of Learning Linear-Quadratic Regulators. CDC Bruce D. Lee, Ingvar M. Ziemann, Anastasios Tsiamis, Henrik Sandberg, Nikolai Matni
2023	J	`jnl`	The Fundamental Limitations of Learning Linear-Quadratic Regulators. CoRR Bruce D. Lee, Ingvar M. Ziemann, Anastasios Tsiamis, Henrik Sandberg, Nikolai Matni
2023	A*	`conf`	The noise level in linear regression with dependent data. NeurIPS Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni
2023	J	`jnl`	The noise level in linear regression with dependent data. CoRR Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni
2022	J	`jnl`	A note on the smallest eigenvalue of the empirical covariance of causal Gaussian processes. CoRR Ingvar M. Ziemann
2022	—	`conf`	How are policy gradient methods affected by the limits of control? CDC Ingvar M. Ziemann, Anastasios Tsiamis, Henrik Sandberg, Nikolai Matni
2022	J	`jnl`	How are policy gradient methods affected by the limits of control? CoRR Ingvar M. Ziemann, Anastasios Tsiamis, Henrik Sandberg, Nikolai Matni
2022	A*	`conf`	Learning to Control Linear Systems can be Hard. COLT Anastasios Tsiamis, Ingvar M. Ziemann, Manfred Morari, Nikolai Matni, George J. Pappas
2022	J	`jnl`	Learning to Control Linear Systems can be Hard. CoRR Anastasios Tsiamis, Ingvar M. Ziemann, Manfred Morari, Nikolai Matni, George J. Pappas
2022	A*	`conf`	Learning with little mixing. NeurIPS Ingvar M. Ziemann, Stephen Tu
2022	J	`jnl`	Learning with little mixing. CoRR Ingvar M. Ziemann, Stephen Tu
2022	J	`jnl`	Regret Lower Bounds for Learning Linear Quadratic Gaussian Systems. CoRR Ingvar M. Ziemann, Henrik Sandberg
2022	A*	`conf`	Single Trajectory Nonparametric Learning of Nonlinear Dynamics. COLT Ingvar M. Ziemann, Henrik Sandberg, Nikolai Matni
2022	J	`jnl`	Single Trajectory Nonparametric Learning of Nonlinear Dynamics. CoRR Ingvar M. Ziemann, Henrik Sandberg, Nikolai Matni
2022	J	`jnl`	Statistical Learning Theory for Control: A Finite Sample Perspective. CoRR Anastasios Tsiamis, Ingvar M. Ziemann, Nikolai Matni, George J. Pappas
2021	—	`conf`	On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix. L4DC Ingvar M. Ziemann, Henrik Sandberg
2021	J	`jnl`	On a Phase Transition of Regret in Linear Quadratic Control: The Memoryless Case. IEEE Control. Syst. Lett. Ingvar M. Ziemann, Henrik Sandberg
2021	C	`conf`	Resource Constrained Sensor Attacks by Minimizing Fisher Information. ACC Ingvar M. Ziemann, Henrik Sandberg
2020	J	`jnl`	On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix. CoRR Ingvar M. Ziemann, Henrik Sandberg
2020	C	`conf`	Parameter Privacy versus Control Performance: Fisher Information Regularized Control. ACC Ingvar M. Ziemann, Henrik Sandberg
2020	J	`jnl`	Regret Lower Bounds for Unbiased Adaptive Control of Linear Quadratic Regulators. IEEE Control. Syst. Lett. Ingvar M. Ziemann, Henrik Sandberg
2019	—	`conf`	Model Reduction of Semistable Distributed Parameter Systems. ECC Ingvar M. Ziemann, Yishao Zhou