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20192023
most citedNeural Architecture Search on Efficient Transformers and Beyond

12 citations · 28 across the 11 of their papers we have counts for

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9 papers · 1 filter

eess.SY2023★ 2 cited

Properties of Immersions for Systems with Multiple Limit Sets with Implications to Learning Koopman Embeddings

Zexiang Liu, Necmiye Ozay, Eduardo D. Sontag

Linear immersions (such as Koopman eigenfunctions) of a nonlinear system have wide applications in prediction and control. In this work, we study the properties of linear immersion…

eess.SY2023

On the Hardness of Learning to Stabilize Linear Systems

Xiong Zeng, Zexiang Liu, Zhe Du +2

Inspired by the work of Tsiamis et al. \cite{tsiamis2022learning}, in this paper we study the statistical hardness of learning to stabilize linear time-invariant systems. Hardness…

eess.SY2023★ 6 cited

Koopman-inspired Implicit Backward Reachable Sets for Unknown Nonlinear Systems

Haldun Balim, Antoine Aspeel, Zexiang Liu +1

Koopman liftings have been successfully used to learn high dimensional linear approximations for autonomous systems for prediction purposes, or for control systems for leveraging l…

eess.SY2023

Quantifying the Value of Preview Information for Safety Control

Zexiang Liu, Necmiye Ozay

Safety-critical systems, such as autonomous vehicles, often incorporate perception modules that can anticipate upcoming disturbances to system dynamics, expecting that such preview…

eess.SY2022

On the Convergence of the Backward Reachable Sets of Robust Controlled Invariant Sets For Discrete-time Linear Systems

Zexiang Liu, Necmiye Ozay

This paper considers discrete-time linear systems with bounded additive disturbances, and studies the convergence properties of the backward reachable sets of robust controlled inv…

eess.SY2021

Automaton-based Implicit Controlled Invariant Set Computation for Discrete-Time Linear Systems

Zexiang Liu, Tzanis Anevlavis, Necmiye Ozay +1

In this paper, we derive closed-form expressions for implicit controlled invariant sets for discrete-time controllable linear systems with measurable disturbances. In particular, a…

eess.SY2021★ 1 cited

On the Value of Preview Information For Safety Control

Zexiang Liu, Necmiye Ozay

Incorporating predictions of external inputs, which can otherwise be treated as disturbances, has been widely studied in control and computer science communities. These predictions…

eess.SY2020★ 1 cited

Scalable Computation of Controlled Invariant Sets for Discrete-Time Linear Systems with Input Delays

Zexiang Liu, Liren Yang, Necmiye Ozay

In this paper, we first propose a method that can efficiently compute the maximal robust controlled invariant set for discrete-time linear systems with pure delay in input. The key…

eess.SY2019

Safety Control with Preview Automaton

Zexiang Liu, Necmiye Ozay

This paper considers the problem of safety controller synthesis for systems equipped with sensor modalities that can provide preview information. We consider switched systems where…