no code implementations • 27 May 2024 • Haojun Wang, Kun Liu, Baojia Li, Emilia Fridman, Yuanqing Xia
Moreover, to analyze the effect of the privacy noise on the detection probability, we consider that each subsystem can estimate the unknown privacy noise covariance by the secondary data.
no code implementations • 14 Apr 2024 • Haosong Peng, Wei Feng, Hao Li, Yufeng Zhan, Qihua Zhou, Yuanqing Xia
In this paper, we find visual foundation models like Vision Transformer (ViT) also have a dedicated acceleration mechanism for video analytics.
no code implementations • 19 Sep 2023 • Yuan Zhang, Yuanqing Xia, Aming Li
This paper explores the structural controllability of switched linear continuous-time systems.
no code implementations • 17 Apr 2023 • Yuan Zhang, Ranbo Cheng, Yuanqing Xia
This paper addresses the problem of determining the minimum set of state variables in a network that need to be blocked from direct measurements in order to protect functional privacy with respect to {\emph{any}} output matrices.
no code implementations • 23 Feb 2023 • Yuan Zhang, Yuanqing Xia, Long Wang
This paper investigates the reachability and controllability of temporal continuous-time linear networks from a generic viewpoint, where only the zero-nonzero patterns of subsystem matrices are known.
no code implementations • 1 Jan 2023 • Qiwen Li, Runze Gao, Yuanqing Xia
In this work, a data-driven predictive cloud controller is developed based on homomorphic encryption to protect the cloud data privacy.
no code implementations • 11 Dec 2022 • Yuhan Suo, Senchun Chai, Runqi Chai, Zhong-Hua Pang, Yuanqing Xia, Guo-Ping Liu
This paper proposes a novel security defense strategy from the perspective of attack detection scheduling to ensure the security of the network.
no code implementations • 16 Sep 2022 • Runze Gao, Qiwen Li, Li Dai, Yufeng Zhan, Yuanqing Xia
First, a construction method for the DPC workflow is designed, to match the distributed processing environment of cloud computing.
no code implementations • 3 Apr 2022 • Yuan Zhang, Yuanqing Xia, Shenyu Liu, Zhongqi Sun
In this paper, it is found that, if the input structure satisfies certain `regularizations', which are characterized by the proposed restricted total unimodulairty notion, those problems can be solvable in polynomial time via linear programming (LP) relaxations.
no code implementations • 4 Jan 2022 • Yuan Zhang, Yuanqing Xia, Yufeng Zhan
This paper addresses the real structured controllability, stabilizability, and stability radii (RSCR, RSSZR, and RSSR, respectively) of linear systems, which involve determining the distance (in terms of matrix norms) between a (possibly large-scale) system and its nearest uncontrollable, unstabilizable, and unstable systems, respectively, with a prescribed affine structure.
no code implementations • 29 Dec 2021 • Runze Gao, Yuanqing Xia, Guan Wang, Liwen Yang, Yufeng Zhan
Subspace identification (SID) has been widely used in system identification and control fields since it can estimate system models only relying on the input and output data by reliable numerical operations such as singular value decomposition (SVD).
no code implementations • 29 Dec 2021 • Runze Gao, Yuanqing Xia, Li Dai, Zhongqi Sun
Nowadays, the rapid increases of the scale and complexity of the controlled plants bring new challenges such as computing power and storage for conventional control systems.
no code implementations • 20 Dec 2021 • Tijin Yan, Tong Zhou, Yufeng Zhan, Yuanqing Xia
With the development of AIoT, data-driven attack detection methods for cyber-physical systems (CPSs) have attracted lots of attention.
no code implementations • 10 Aug 2021 • Yuan Zhang, Yuanqing Xia, Yufeng Zhan
Subject to a certain condition on the prescribed input configurations that contains the dedicated input one as a special case, we demonstrate that the constraint matrices of these ILPs are totally unimodular.
no code implementations • 4 Jul 2021 • Hongwei Zhang, Weidong Zou, Hongbo Zhao, Qi Ming, Tijin Yan, Yuanqing Xia, Weipeng Cao
Inspired by this, we propose AdaL, with a transformation on the original gradient.
no code implementations • 26 Jun 2021 • Yuan Zhang, Yuanqing Xia
This paper introduces a new controllability notion, termed partial strong structural controllability (PSSC), on a structured system whose entries of system matrices are either fixed zero or indeterminate, which naturally extends the conventional strong structural controllability (SSC) and bridges the gap between structural controllability and SSC.
1 code implementation • 18 Jun 2021 • Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, Yuanqing Xia
However, many existing works can not be widely used because of the constraints of functional form of generative models or the sensitivity to hyperparameters.
no code implementations • 22 Mar 2021 • Yuan Zhang, Yuanqing Xia
This paper proposes a novel notion for structural controllability under structured numerical perturbations, namely the perturbation-tolerant structural controllability (PTSC), on a single-input structured system whose entries can be classified into three categories: fixed zero entries, unknown generic entries whose values are fixed but unknown, and perturbed entries that can take arbitrary complex values.
no code implementations • 11 Mar 2021 • Ning Zhou, Xiaodong Cheng, Zhongqi Sun, Yuanqing Xia
In this paper, we investigate the fixed-time behavioral control problem for a team of second-order nonlinear agents, aiming to achieve a desired formation with collision/obstacle~avoidance.
Optimization and Control
no code implementations • 24 Sep 2020 • Hongwei Zhang, Tijin Yan, Zenjun Xie, Yuanqing Xia, Yuan Zhang
Based on our theoretical and empirical analysis, we establish a universal theoretical framework of GCN from an optimization perspective and derive a novel convolutional kernel named GCN+ which has lower parameter amount while relieving the over-smoothing inherently.
no code implementations • 1 Sep 2020 • Tijin Yan, Hongwei Zhang, Zirui Li, Yuanqing Xia
In addition, to alleviate KL-vanishing problem in SGRNN, a simple and interpretable structure is proposed based on the lower bound of KL-divergence.
1 code implementation • 23 Nov 2018 • Jiang Zhang, Yuanqing Xia, Ganghui Shen
Autonomous path planning algorithms are significant to planetary exploration rovers, since relying on commands from Earth will heavily reduce their efficiency of executing exploration missions.
no code implementations • 25 Aug 2018 • Jiang Zhang, Yuanqing Xia, Ganghui Shen
In this paper, emerging deep learning techniques are leveraged to deal with Mars visual navigation problem.