12 citations · 33 across the 13 of their papers we have counts for
15 papers
Design of Privacy-Preserving Estimators Under Prior Information Exposure
Le Liu, Yu Kawano, Ming Cao
State estimation is widely used in networked dynamical systems, but released estimates may inadvertently reveal sensitive information about private state variables. Existing privac…
A Randomized Scheduling Framework for Privacy-Preserving Multi-robot Rendezvous given Prior Information
Le Liu, Yu Kawano, Ming Cao
Privacy has become a critical concern in modern multi-robot systems, driven by both ethical considerations and operational constraints. As a result, growing attention has been dire…
Privacy protection under the exposure of systems' prior information
Le Liu, Yu Kawano, Ming Cao
For systems whose states implicate sensitive information, their privacy is of great concern. While notions like differential privacy have been successfully introduced to dynamical…
Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
Le Liu, Yu Kawano, Antai Xie +1
In this paper, we investigate initial state privacy protection for discrete-time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy cha…
Distributionally Robust Model Order Reduction for Linear Systems
Le Liu, Yu Kawano, Yangming Dou +1
In this paper, we investigate distributionally robust model order reduction for linear, discrete-time, time-invariant systems. The external input is assumed to follow an uncertain…
Privacy Preservation for Statistical Input in Dynamical Systems
Le Liu, Yu Kawano, Ming Cao
This paper addresses the challenge of privacy preservation for statistical inputs in dynamical systems. Motivated by an autonomous building application, we formulate a privacy pres…
Design of Stochastic Quantizers for Privacy Preservation
Le Liu, Yu Kawano, Ming Cao
In this paper, we examine the role of stochastic quantizers for privacy preservation. We first employ a static stochastic quantizer and investigate its corresponding privacy-preser…
Learning Stabilizable Deep Dynamics Models
Kenji Kashima, Ryota Yoshiuchi, Yu Kawano
When neural networks are used to model dynamics, properties such as stability of the dynamics are generally not guaranteed. In contrast, there is a recent method for learning the d…
Stability of Remote Synchronization in Star Networks of Kuramoto Oscillators
Yuzhen Qin, Yu Kawano, Ming Cao
Synchrony of neuronal ensembles is believed to facilitate information exchange among cortical regions in the human brain. Recently, it has been observed that distant brain areas wh…
Scalable Control Design for K-positive Linear Systems
Yu Kawano, Fulvio Forni
Systems whose variable are constrained to be positive allow computationally efficient control design. We generalize these results to linear systems which leave a cone invariant. Th…
Partial Exponential Stability Analysis of Slow-fast Systems via Periodic Averaging
Yuzhen Qin, Yu Kawano, Brian D. O. Anderson +1
This paper presents some new criteria for partial exponential stability of a slow-fast nonlinear system with a fast scalar variable using periodic averaging methods. Unlike classic…
Asynchronous and time-varying proximal type dynamics multi-agent network games
Carlo Cenedese, Giuseppe Belgioioso, Yu Kawano +2
In this paper, we study proximal type dynamics in the context of noncooperative multi-agent network games. These dynamics arise in different applications, since they describe distr…
Partial Phase Cohesiveness in Networks of Kuramoto Oscillator Networks
Yuzhen Qin, Yu Kawano, Oscar Portoles +1
Partial, instead of complete, synchronization has been widely observed in various networks including, in particular, brain networks. Motivated by data from human brain functional n…
Design of Privacy-Preserving Dynamic Controllers
Yu Kawano, Ming Cao
As a quantitative criterion for privacy of "mechanisms" in the form of data-generating processes, the concept of differential privacy was first proposed in computer science and has…
Towards time-varying proximal dynamics in Multi-Agent Network Games
Carlo Cenedese, Yu Kawano, Sergio Grammatico +1
Distributed decision making in multi-agent networks has recently attracted significant research attention thanks to its wide applicability, e.g. in the management and optimization…