Matni, Nikolai

30 publications

L4DC 2025 Domain Randomization Is Sample Efficient for Linear Quadratic Control Tesshu Fujinami, Bruce D. Lee, Nikolai Matni, George J. Pappas

L4DC 2025 Logarithmic Regret for Nonlinear Control James Wang, Bruce Lee, Ingvar Ziemann, Nikolai Matni

ICML 2025 On the Concurrence of Layer-Wise Preconditioning Methods and Provable Feature Learning Thomas Tck Zhang, Behrad Moniri, Ansh Nagwekar, Faraz Rahman, Anton Xue, Hamed Hassani, Nikolai Matni

AAAI 2025 Regret Analysis of Multi-Task Representation Learning for Linear-Quadratic Adaptive Control Bruce D. Lee, Leonardo F. Toso, Thomas T. Zhang, James Anderson, Nikolai Matni

L4DC 2025 State Space Models, Emergence, and Ergodicity: How Many Parameters Are Needed for Stable Predictions? Ingvar Ziemann, Nikolai Matni, George Pappas

WACV 2024 EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields Anish Bhattacharya, Ratnesh Madaan, Fernando Cladera, Sai Vemprala, Rogerio Bonatti, Kostas Daniilidis, Ashish Kapoor, Vijay Kumar, Nikolai Matni, Jayesh K. Gupta

ICML 2024 Guarantees for Nonlinear Representation Learning: Non-Identical Covariates, Dependent Data, Fewer Samples Thomas Tck Zhang, Bruce D Lee, Ingvar Ziemann, George J. Pappas, Nikolai Matni

CoRL 2024 Monocular Event-Based Vision for Obstacle Avoidance with a Quadrotor Anish Bhattacharya, Marco Cannici, Nishanth Rao, Yuezhan Tao, Vijay Kumar, Nikolai Matni, Davide Scaramuzza

L4DC 2024 Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with Model Misspecification Bruce Lee, Anders Rantzer, Nikolai Matni

ICLR 2024 Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data Thomas TCK Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni

ICML 2024 Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss Ingvar Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni

L4DC 2023 Learning-Enhanced Nonlinear Model Predictive Control Using Knowledge-Based Neural Ordinary Differential Equations and Deep Ensembles Kong Yao Chee, M. Ani Hsieh, Nikolai Matni

L4DC 2023 Multi-Task Imitation Learning for Linear Dynamical Systems Thomas T. Zhang, Katie Kang, Bruce D Lee, Claire Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni

NeurIPS 2023 The Noise Level in Linear Regression with Dependent Data Ingvar Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni

ICML 2023 The Power of Learned Locally Linear Models for Nonlinear Policy Optimization Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu

L4DC 2022 Adversarially Robust Stability Certificates Can Be Sample-Efficient Thomas Zhang, Stephen Tu, Nicholas Boffi, Jean-Jacques Slotine, Nikolai Matni

L4DC 2022 Generalization Bounded Implicit Learning of Nearly Discontinuous Functions Bibit Bianchini, Mathew Halm, Nikolai Matni, Michael Posa

COLT 2022 Learning to Control Linear Systems Can Be Hard Anastasios Tsiamis, Ingvar M Ziemann, Manfred Morari, Nikolai Matni, George J. Pappas

L4DC 2022 On the Sample Complexity of Stability Constrained Imitation Learning Stephen Tu, Alexander Robey, Tingnan Zhang, Nikolai Matni

COLT 2022 Single Trajectory Nonparametric Learning of Nonlinear Dynamics Ingvar M Ziemann, Henrik Sandberg, Nikolai Matni

NeurIPS 2022 TaSIL: Taylor Series Imitation Learning Daniel Pfrommer, Thomas Zhang, Stephen Tu, Nikolai Matni

NeurIPSW 2022 Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based RL David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley

L4DC 2021 Data-Driven System Level Synthesis Anton Xue, Nikolai Matni

L4DC 2021 How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? Jingxi Xu, Bruce Lee, Nikolai Matni, Dinesh Jayaraman

CoRL 2020 Learning Hybrid Control Barrier Functions from Data Lars Lindemann, Haimin Hu, Alexander Robey, Hanwen Zhang, Dimos Dimarogonas, Stephen Tu, Nikolai Matni

CoRL 2020 Learning Stability Certificates from Data Nicholas Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques Slotine, Vikas Sindhwani

ICLR 2020 PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction Sangdon Park, Osbert Bastani, Nikolai Matni, Insup Lee

L4DC 2020 Robust Guarantees for Perception-Based Control Sarah Dean, Nikolai Matni, Benjamin Recht, Vickie Ye

L4DC 2020 Sample Complexity of Kalman Filtering for Unknown Systems Anastasios Tsiamis, Nikolai Matni, George Pappas

NeurIPS 2018 Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu