← Authors

Nikolai Matni

29 papers · 2018–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (8) 🐝 Cross-Pollinator (13) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (7) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🀝 Dynamic Duo (10) πŸ† Grand Slam πŸ† Keyword Champion (4) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (6) ⚑ Prolific Year (5) ❓ The Questioner (2) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (90) πŸ’Ž Century Club (29)

Conferences

L4DC (13) ICML (4) CORL (3) NIPS (3) COLT (2) ICLR (2) AAAI (1) WACV (1)

Top co-authors

Stephen Tu (10) George J. Pappas (5) Ingvar Ziemann (5) Thomas TCK Zhang (3) Bruce Lee (3) Alexander Robey (2) Nicholas Boffi (2) James Anderson (2) Thomas Zhang (2) Vijay Kumar (2)

Research topics

Robotics (2) Reinforcement Learning (1)

Keywords

sample complexity (5) system identification (4) adaptive control (4) sample efficiency (3) imitation learning (3) robust control (2) regret analysis (2) stability certificate (2) representation learning (2) multi-task learning (2) reinforcement learning (2) nonlinear dynamics (2) online learning (2) generalization bound (2) continuous control (2) policy optimization (2) linear quadratic regulator (2) state estimation (2) optimal control (2) model predictive control (1)

Papers

Domain Randomization is Sample Efficient for Linear Quadratic Control L4DC 2025
Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control AAAI 2025
Logarithmic Regret for Nonlinear Control L4DC 2025
State space models, emergence, and ergodicity: How many parameters are needed for stable predictions? L4DC 2025
On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning ICML 2025
EvDNeRF: Reconstructing Event Data With Dynamic Neural Radiance Fields WACV 2024
Monocular Event-Based Vision for Obstacle Avoidance with a Quadrotor CORL 2024
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data ICLR 2024
Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples ICML 2024
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss ICML 2024
Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification L4DC 2024
Multi-Task Imitation Learning for Linear Dynamical Systems L4DC 2023
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization ICML 2023
The noise level in linear regression with dependent data NIPS 2023
Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles L4DC 2023
Adversarially Robust Stability Certificates can be Sample-Efficient L4DC 2022
TaSIL: Taylor Series Imitation Learning NIPS 2022
On the Sample Complexity of Stability Constrained Imitation Learning L4DC 2022
Generalization Bounded Implicit Learning of Nearly Discontinuous Functions L4DC 2022
Single Trajectory Nonparametric Learning of Nonlinear Dynamics COLT 2022
Learning to Control Linear Systems can be Hard COLT 2022
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? L4DC 2021
Data-Driven System Level Synthesis L4DC 2021
Learning Hybrid Control Barrier Functions from Data CORL 2020
Sample Complexity of Kalman Filtering for Unknown Systems L4DC 2020
Robust Guarantees for Perception-Based Control L4DC 2020
Learning Stability Certificates from Data CORL 2020
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction ICLR 2020
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator NIPS 2018