24 papers
Robust Conformal CBF and CLF Controllers via Iterative Policy Updates
Omid Mirzaeedodangeh, Eliot Shekhtman, Nikolai Matni +1
Conformal prediction (CP) has been used to obtain probabilistic bounds on the error between a learned dynamics model and the true but unknown system. Such CP bounds can then be emb…
Double Preconditioning (DoPr): Optimization for Test-Time Performance, not Validation Loss
Thomas T. Zhang, Alok Shah, Yifei Zhang +3
Many modern applications of deep learning involve training a neural network via a one-step prediction loss (e.g., regression, cross-entropy), but deploy the network by rollin…
The Fragility of Learning LQG Controllers
Bruce D. Lee, Anastasios Tsiamis, Nikolai Matni +2
Learning methods are increasingly used to synthesize controllers from data, yet existing sample-complexity characterizations for continuous control are sharp only in the fully obse…
Near-optimal Online Traffic Engineering
Arvin Ghavidel, Pooria Namyar, Nikolai Matni +2
Most deployed WAN Traffic Engineering (TE) systems use a logically centralized controller that periodically gathers traffic demands, runs a TE optimization or heuristic, and then p…
A Quantitative Framework for Navigating Controller Design Tradeoffs under Computational Constraints
Chris Verhoek, Nikolai Matni
Computational constraints permeate the controller design process, and yet are rarely treated as explicit design constraints. Towards addressing this gap, we propose a quantitative…
Safe Planning in Interactive Environments via Iterative Policy Updates and Adversarially Robust Conformal Prediction
Omid Mirzaeedodangeh, Eliot Shekhtman, Nikolai Matni +1
Safe planning of an autonomous agent in interactive environments -- such as the control of a self-driving vehicle among pedestrians -- poses a major challenge as the behavior of th…